Infonorma is a multi-agent system that provides its users with recommendations of legal normative instruments they might be interested in. The Filter agent of Infonorma classifies normative instruments represented as Semantic Web documents into legal branches and performs content-based similarity analysis. This agent, as well as the entire Infonorma system, was modeled under the guidelines of MAAEM, a software development methodology for multi-agent application engineering. This article describes the Infonorma requirements specification, the architectural design solution for those requirements, the detailed (...) design of the Filter agent and the implementation model of Infonorma, according to the guidelines of the MAAEM methodology. (shrink)

This article analyses the ethical aspects of multistakeholder recommendation systems (RSs). Following the most common approach in the literature, we assume a consequentialist framework to introduce the main concepts of multistakeholder recommendation. We then consider three research questions: who are the stakeholders in a RS? How are their interests taken into account when formulating a recommendation? And, what is the scientific paradigm underlying RSs? Our main finding is that multistakeholder RSs (MRSs) are designed and theorised, methodologically, according to neoclassical (...) welfare economics. We consider and reply to some methodological objections to MRSs on this basis, concluding that the multistakeholder approach offers the resources to understand the normative social dimension of RSs. (shrink)

This is the third draft of a paper that aims to clarify the apparent contradictions in the views presented in certain standards and other specifications of health informatics systems, contradictions which come to light when the latter are evaluated from the perspective of realist philosophy. One of the origins of this document was Klein’s discussion paper of 2005-07-02 entitled “Conceptology vs Reality” and the responses from Smith, as well as the several hours of discussions during the 2005 MIE meeting (...) in Geneva. (shrink)

The framework of the ‘social ontology of the internet’ is applied to music recommendation platforms. Those websites provide individual suggestions of music to users, creating new dynamics of taste that are no longer based on human-to-human interaction and verbalized judgments. An exemplary analysis of three platforms shows that different conceptions of musical tastes are represented by technical systems: situational emotional preferences, a formalist aesthetics, and social proximity based on tastes. The platforms share certain assumptions about the ontology (...) of musical entities and of course the constitutive act of recommending. We discuss how this act can be ascribed to technical systems. Theses on the platforms’ effects on the social structure of musical tastes are developed. (shrink)

In the recruitment process, manually selecting suitable candidates from curriculum vitae (CVs) for a job description (JD) is both time-consuming and expensive. Traditional keyword-based methods struggle to capture skill semantics, prompting the development of more advanced JD-CV matching systems. This paper aims to investigate and construct an ontology-based skills recommendation system, with objectives including creating a skills ontology and developing skills matching methods for JD-CV pairs. The objective of our approach is to enhance the accuracy and contextual (...) relevance of recommendations by utilizing the proposed score. The proposed skills ontology and skills matching strategies are applied to a real dataset in Vietnam. The results of our study can automatically recommend a list of CVs for a given JD. Furthermore, the findings indicate that our proposed model surpasses comparative approaches by a margin of at least 1% to 5%. Overall, the study demonstrates the potential of utilizing ontology-based approaches to offer a practical solution for enhancing hiring practices. (shrink)

With the rapid development of information technology and data science, as well as the innovative concept of “Internet+” education, personalized e-learning has received widespread attention in school education and family education. The development of education informatization has led to a rapid increase in the number of online learning users and an explosion in the number of learning resources, which makes learners face the dilemma of “information overload” and “learning lost” in the learning process. In the personalized learning resource recommendation system, (...) the most critical thing is the construction of the learner model. Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. The purpose of this paper is to construct a learner model to support the above problems and to strongly support individual learning resources recommendation by learning the resource model which effectively reduces the problem of cold start and sparsity in the recommended process. In this paper, we analyze the behavioral data of learners in the learning process and extract three features of learner’s cognitive ability, knowledge level, and preference for learning of learner model analysis. Among them, the preference model of the learner is constructed using the ontology, and the semantic relation between the knowledge is better understood, and the interest of the student learning is discovered. (shrink)

The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In (...) the naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable. (shrink)

Formal Ontology is a discipline whose business is to develop formal theories about general aspects of reality such as identity, dependence, parthood, truth-making, causality, etc. A foundational ontology is a specific consistent set of these ontological theories that support activities such as domain analysis, conceptual clarification, and meaning negotiation. A (well-founded) core ontology specifies, under a foundational ontology, the central concepts and relations of a given domain. Foundational and core ontologies can be seen as ontology (...) engineering frameworks to systematically address the laborious task of building large (more specific) domain ontologies. However, both in research and industry, it is common that ontologies as computational artifacts are built without the aid of any framework of this kind, often yielding modeling mistakes and representation gaps. In this paper, we analyze a case in the domain of cybersecurity, namely, the case of D3FEND — an OWL knowledge graph of cybersecurity countermeasure techniques proposed by the MITRE Corporation. Based on the Reference Ontology for Security Engineering (ROSE), a core ontology of the security domain founded in the Unified Founda-tional Ontology (UFO), our investigation reveals a number of semantic issues and opportunities for improvement in D3FEND, including missing concepts, semantic overload of terms, and lacking constraints that cause an under-specification of the model. As a result of our ontological analysis, we propose several suggestions for the appropriate redesign of D3FEND to overcome those issues. (shrink)

Objectives: Medical decision support and other intelligent applications in the life sciences depend on increasing amounts of digital information. Knowledge bases as well as formal ontologies are being used to organize biomedical knowledge and data. However, these two kinds of artefacts are not always clearly distinguished. Whereas the popular RDF(S) standard provides an intuitive triple-based representation, it is semantically weak. Description logics based ontology languages like OWL-DL carry a clear-cut semantics, but they are computationally expensive, and they are often (...) misinterpreted to encode all kinds of statements, including those which are not ontological. Method: We distinguish four kinds of statements needed to comprehensively represent domain knowledge: universal statements, terminological statements, statements about particulars and contingent statements. We argue that the task of formal ontologies is solely to represent universal statements, while the non-ontological kinds of statements can nevertheless be connected with ontological representations. To illustrate these four types of representations, we use a running example from parasitology. Results: We finally formulate recommendations for semantically adequate ontologies that can efficiently be used as a stable framework for more context-dependent biomedical knowledge representation and reasoning applications like clinical decision support systems. (shrink)

The institutions we create shape many of the activities we engage insofar as they are pervasive entities in our society. In an era full of new technologies, including the semantic web, there is a movement toward sound conceptual modeling for socio-technical solutions applied to government institutions. To develop these complex solutions, one needs to deepen the ontological status of entities in the institutional domain, because literature is full of ambiguous and ad-hoc hypotheses about distinctions between public and private corporations. We (...) believe we can find better explanations for such distinctions in the interdisciplinary field of library a information science. Within an ongoing semantic web project, we focus on a study case of official documents. First, we analyze theories about public and private corporations, seeking a reliable on‘tological distinction between them; then, by focusing on documents produced by each type of corporation, we hope to provide a well-founded analysis. Second, we adopt the aforementioned theories and the new analysis as recommendations for the improvement for the access and understanding of public documents, through appropriate classification of them within government information systems. This project, ultimately, aims to maximize the transparency of public government documents by favoring retrieval and comprehension by a society with plenty of automated information systems. (shrink)

Evidence-based medicine relies on the execution of clinical practice guidelines and protocols. A great deal of of effort has been invested in the development of various tools which automate the representation and execution of the recommendations contained within such guidelines and protocols by creating Computer Interpretable Guideline Models (CIGMs). Context-based task ontologies (CTOs), based on standard terminology systems like UMLS, form one of the core components of such a model. We have created DAML+OIL-based CTOs for the tasks mentioned in (...) the WHO guideline for hypertension management, drawing comparisons also with other related guidelines. The advantages of CTOs include: contextualization of ontologies, providing ontologies tailored to specific aspects of the phenomena of interest, dividing the complexity involved in creating ontologies into different levels, providing a methodology by means of which the task recommendations contained within guidelines can be integrated into the clinical practices of a health care set-up. (shrink)

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system.

There have been a number of recent attempts to identify the best metaphysical framework for capturing Rovelli’s Relational Quantum Mechanics (RQM). All such accounts commit to some form of fundamentalia, whether they be traditional objects, physical relations, events or ‘flashes’, or the cosmos as a fundamental whole. However, Rovelli’s own recommendation is that ‘a natural philosophical home for RQM is an anti-foundationalist perspective' (Rovelli in Philos Trans R Soc 376:10, 2018). This gives us some prima facie reason to explore options (...) beyond these foundationalist frameworks, and take seriously a picture that lacks fundamentalia. I construct an argument from elimination in favour of an anti-foundationalist interpretation of RQM. The argument notes that _priority monism_ and _priority pluralism_ are exhaustive foundationalist options, and then shows that there are reasons to reject their union with RQM. I finish by recommending _metaphysical coherentism_ as a promising anti-foundationalist alternative, which captures the key characteristics of RQM through accepting symmetrical dependence, whilst avoiding challenges by jettisoning any commitment to fundamental entities. (shrink)

In recent years, social networks have made significant progress and the number of people who use them to communicate is increasing day by day. The vast amount of information available on social networks has led to the importance of using friend recommender systems to discover knowledge about future communications. It is challenging to choose the best machine learning approach to address the recommender system issue since there are several strategies with various benefits and drawbacks. In light of (...) this, a solution based on the stacking approach was put out in this study to provide a buddy recommendation system in social networks. Additionally, a decrease in system performance was caused by the large amount of information that was accessible and the inefficiency of some functions. To solve this problem, a particle swarm optimization algorithm to select the most efficient features was used in our proposed method. To learn the model in the objective function of the particle swarm algorithm, a hybrid system based on stacking is proposed. In this method, two random forests and Extreme Gradient Boosting had been used as the base classifiers. The results obtained from these base classifiers were used in the logistic regression algorithm, which has been applied sequentially. The suggested approach was able to effectively address this issue by combining the advantages of the applied strategies. The results of implementation and evaluation of the proposed system show the appropriate efficiency of this method compared with other studied techniques. (shrink)

This open access contributed volume examines the ethical and legal foundations of (future) policies on recommender systems and offers a transdisciplinary approach to tackle important issues related to their development, use and integration into online eco-systems. This volume scrutinizes the values driving automated recommendations - what is important for an individual receiving the recommendation, the company on which that platform was received, and society at large might diverge. The volume addresses concerns about manipulation of individuals and risks (...) for personal autonomy. From a legal perspective, the volume offers a much-needed evaluation of regulatory needs and lawmakers’ answers in various legal disciplines. The focus is on European Union measures of platform regulation, consumer protection and anti-discrimination law. The volume will be of particular interest to the community of legal scholars dealing with platform regulation and algorithmic decision making. By including specific use cases, the volume also exposes pitfalls associated with current models of regulation. Beyond the juxtaposition of purely ethical and legal perspectives, the volume contains truly interdisciplinary work on various aspects of recommender systems. (shrink)

With the rapid development of the Internet, recommendation systems have received widespread attention as an effective way to solve information overload. Social tagging technology can both reflect users’ interests and describe the characteristics of the items themselves, making group recommendation thus becoming a recommendation technology in urgent demand nowadays. In traditional tag-based recommendation systems, the general processing method is to calculate the similarity and then rank the recommended items according to the similarity. Without considering the influence of continuous (...) user behavior, in this article, we propose a personalized recommendation algorithm based on social tags by combining the ideas of Markov chain and collaborative filtering. This algorithm splits the three-dimensional relationship of into two two-dimensional relationships of and. The user’s interest degree to the tags is calculated by the Markov chain model, and then the items corresponding to them are matched by the recommended tag set. The influence between tags is used to model the satisfaction of items based on the correlation between the tags contained in the matched items, and collaborative filtering is used to complete the sparse values when calculating the interest and satisfaction between user–tags and user–items to improve the accuracy of recommendations. The experiments show that in the publicly available dataset, the personalized recommendation algorithm proposed in this article has significantly improved in accuracy and recall rate compared with the existing algorithms. (shrink)

PurposeThe paper aims to examine the profound transformations engendered by the information revolution in order to determine aspects of what should be visible or invisible in human affairs. It seeks to explore the meaning of invisibility via an interdisciplinary approach, including computer science, law, and ethics.Design/methodology/approachThe method draws on both theoretical and empirical material so as to scrutinise the ways in which today's information revolution is recasting the boundaries between visibility and invisibility.FindingsThe degrees of exposure to public notice can be (...) understood as a matter of balance between access and control over information in a specific context, as well as a function of the ontological friction in a given region of the environment.Originality/valueThe originality of the case study on a new kind of recommender system is enhanced because of the procedural approach which is suggested to further develop the distinction between “good” and “evil” as anything that enriches, or damages, the informational complexity of the environment. (shrink)

Recommender systems assist users in receiving preferred or relevant services and information. Using such technology could be instrumental in addressing the lack of relevance digital mental health apps have to the user, a leading cause of low engagement. However, the use of recommender systems for digital mental health apps, particularly those driven by personal data and artificial intelligence, presents a range of ethical considerations. This paper focuses on considerations particular to the juncture of recommender (...) class='Hi'>systems and digital mental health technologies. While separate bodies of work have focused on these two areas, to our knowledge, the intersection presented in this paper has not yet been examined. This paper identifies and discusses a set of advantages and ethical concerns related to incorporating recommender systems into the digital mental health ecosystem. Advantages of incorporating recommender systems into DMH apps are identified as a reduction in choice overload, improvement to the digital therapeutic alliance, and increased access to personal data & self-management. Ethical challenges identified are lack of explainability, complexities pertaining to the privacy/personalization trade-off and recommendation quality, and the control of app usage history data. These novel considerations will provide a greater understanding of how DMH apps can effectively and ethically implement recommender systems. (shrink)

Despite their ethical challenges, recommender systems (RS) are widely endorsed as a necessary solution to the problem of information overload. After clarifying how the harmful effects of information overload can be characterized in distinct ways, I explore the often overlooked potential benefits of abundant online spaces. I argue that these spaces afford valuable opportunities to experience spontaneous freedom. I then put forth a more comprehensive evaluation of the role RS should assume in algorithmically structuring the online space. This (...) evaluation aims to reconcile the dual objectives of mitigating the harms of information overload and preserving opportunities to experience spontaneous freedom. (shrink)

The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not (...) unique to last.fm but stem from certain properties shared by all recommendation systems. Furthermore, unlike other oft-studied digital/web technologies of the self which facilitate ‘self-publishing’ vis-à-vis virtual companions in social media, recommender algorithms themselves can act as ‘intimate experts’, accompanying users in their self-care practices. Thus, recommendation systems can facilitate both algorithmic control and creative self-transformation, which calls for a theorization of this new cultural medium as a space of tension. (shrink)

Recommender Systems (RecSys) have been around since the early days of the Internet, helping users navigate the vast ocean of information and the increasingly available options that have been available for us ever since. The range of tasks for which one could use a RecSys is expanding as the technical capabilities grow, with the disruption of Machine Learning representing a tipping point in this domain, as in many others. However, the increase of the technical capabilities of AI-powered RecSys (...) did not come with a thorough consideration of their ethical implications and, despite being a well-established technical domain, the potential impacts of RecSys on their users are still under-assessed. This paper aims at filling this gap in regards to one of the main impacts of RecSys: personal autonomy. We first describe how technology can affect human values and a suitable methodology to identify these effects and mitigate potential harms: Value Sensitive Design (VSD). We use VSD to carry out a conceptual investigation of personal autonomy in the context of a generic RecSys and draw on a nuanced account of procedural autonomy to focus on two components: competence and authenticity. We provide the results of our inquiry as a value hierarchy and apply it to the design of a speculative RecSys as an example. (shrink)

The growing diffusion of perspectivism within the debate on information system ontologies [ISOs] does not correspond to a thorough analysis of what perspectivism specifically consists of. This paper aims to fill this void. First, I show what supporting perspectivism in information system ontologies [PISO] means in terms of (minimal) claims and implications; then I argue that the definitions of ISO implicitly assume PISO’s (minimal) claims or, in other words, that ISOs presuppose and maintain PISO. Section 2 presents the main definitions (...) of ISO. Section 3 specifies what claims are common to all perspectivists in ISO. Sects. 4–7 analyze the implications of those claims. Section 8 explores the chance of multiple perspectivisms within ISOs’ domain. Finally, Sects. 9–10 assume that, if PISO’s (minimal) claims and (their) implications can be inferred from ISO’s definitions, then ISOs are perspectivist, or PISO’s minimal claims are assumptions underlying ISOs. (shrink)

Although personal and group recommendation systems have been quickly developed recently, challenges and limitations still exist. In particular, users constantly explore new items and change their preferences throughout time, which causes difficulties in building accurate user profiles and providing precise recommendation outcomes. In this context, this study addresses the time awareness of the user preferences and proposes a hybrid recommendation approach for both individual and group recommendations to better meet the user preference changes and thus improve the recommendation performance. (...) The experimental results show that the proposed approach outperforms several baseline algorithms in terms of precision, recall, novelty, and diversity, in both personal and group recommendations. Moreover, it is clear that the recommendation performance can be largely improved by capturing the user preference changes in the study. These findings are beneficial for increasing the understanding of the user dynamic preference changes in building more precise user profiles and expanding the knowledge of developing more effective and efficient recommendation systems. (shrink)

Health Recommender Systems are promising Articial-Intelligence-based tools endowing healthy lifestyles and therapy adherence in healthcare and medicine. Among the most supported areas, it is worth mentioning active aging. However, current HRS supporting AA raise ethical challenges that still need to be properly formalized and explored. This study proposes to rethink HRS for AA through an autonomy-based ethical analysis. In particular, a brief overview of the HRS’ technical aspects allows us to shed light on the ethical risks and challenges (...) they might raise on individuals’ well-being as they age. Moreover, the study proposes a categorization, understanding, and possible preventive/mitigation actions for the elicited risks and challenges through rethinking the AI ethics core principle of autonomy. Finally, elaborating on autonomy-related ethical theories, the paper proposes an autonomy-based ethical framework and how it can foster the development of autonomy-enabling HRS for AA. (shrink)

Recommender system depends on the thoughts of numerous users to predict the favourites of potential consumers. RS is vulnerable to malicious information. Unsuitable products can be offered to the user by injecting a few unscrupulous “shilling” profiles like push and nuke attacks into the RS. Injection of these attacks results in the wrong recommendation for a product. The aim of this research is to develop a framework that can be widely utilized to make excellent recommendations for sales growth. This (...) study uses the methodology that presents an enhanced clustering algorithm named as modified density peak clustering algorithm on the consumer review dataset to ensure a well-formed cluster. An improved recurrent neural network algorithm is proposed to detect these attacks in hybrid RS, which uses the content-based RS and collaborative filtering RS. The results are compared with other state of the art algorithms. The proposed method is more suitable for E-commerce applications where the number of customers and products grows rapidly. (shrink)

Decisions are taken by humans very often during professional as well as leisure activities. It is particularly evident during surfing the Internet: selecting web sites to explore, choosing needed information in search engine results or deciding which product to buy in an on-line store. Recommender systems are electronic applications, the aim of which is to support humans in this decision making process. They are widely used in many applications: adaptive WWW servers, e-learning, music and video preferences, internet stores (...) etc. In on-line solutions, such as e-shops or libraries, the aim of recommendations is to show customers the products which they are probably interested in. As input data the following are taken: shopping basket archives, ratings of the products or servers log files.The article presents a solution of recommender system which helps users to select an interesting product. The system analyses data from other customers' ratings of the products. It uses clustering methods to find similarities among the users and proposed techniques to identify users' profiles. The system was implemented in Apache Mahout environment and tested on a movie database. Selected similarity measures are based on: Euclidean distance, cosine as well as correlation coefficient and loglikehood function. (shrink)

Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries’ data of the International Trade Network. A recommendation system is then used to identify the products that correspond to the production capacity of each individual country but are somehow overlooked (...) by the country. Then, we simulate the evolution of the country’s fitness if it would have followed the recommendations. The result of this work is the combination of these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries. (shrink)

Up to 70% of all watch time on YouTube is due to the suggested content of its recommender system. This system has been found, by virtue of its design, to be promoting conspiratorial content. In this paper, I first critique the value neutrality thesis regarding technology, showing it to be philosophically untenable. This means that technological artefacts can influence what people come to value (or perhaps even embody values themselves) and change the moral evaluation of an action. Second, I (...) introduces the concept of an affordance, borrowed from the literature on ecological psychology. This concept allows me to make salient how technologies come to solicit certain kinds of actions from users, making such actions more or less likely, and in this way influencing the kinds of things one comes to value. Third, I critically assesses the results of a study by Alfano et al. I make use of the literature on affordances, introduced earlier, to shed light on how these technological systems come to mediate our perception of the world and influence action. (shrink)

I aim to illustrate how the recommender systems of digital platforms create a particularly problematic kind of vulnerability in their users. Specifically, through theories of scaffolded cognition and scaffolded affectivity, I argue that a digital platform’s recommender system is a cognitive and affective artifact that fulfills different functions for the platform’s users and its designers. While it acts as a content provider and facilitator of cognitive, affective and decision-making processes for users, it also provides a continuous and (...) detailed amount of information to platform designers regarding users’ cognitive and affective processes. This dynamic, I argue, engenders a kind of vulnerability in platform users, structuring a power imbalance between designers and users. This occurs because the recommender system can not only gather data on users’ cognitive and affective processes, but also affects them in an unprecedentedly economic and capillary manner. By examining one instance of ethically problematic practice from Facebook, I specifically argue that rather than being a tool for manipulating or exploiting people, digital platforms, especially by their underlying recommender systems, can single out and tamper with specific cognitive and affective processes as a tool specifically designed for mind invasion. I conclude by reflecting how the understanding of such AI systems as tools for mind invasion highlights some merits and shortcomings of the AI Act with regards to the protection of vulnerable people. (shrink)

With the deployment of information and communication technologies and the needs of data and information sharing within cities, smart city aims to provide value-added services to improve citizens’ quality of life. But, currently city planners/developers are faced with inadequate contextual information on the dimensions of smart city required to achieve a sustainable society. Therefore, in achieving sustainable society, there is need for stakeholders to make strategic decisions on how to implement smart city initiatives. Besides, it is required to specify the (...) smart city dimensions to be adopted in making cities smarter for sustainability attainment. But, only a few methods such as big data, internet of things, cloud computing, etc. have been employed to support smart city attainment. Thus, this study integrates case-based reasoning as an artificial intelligence technique to develop a recommender system towards promoting smart city planning. CBR provides suggestions on smart city dimensions to be adopted by city planners/decision-makers in making cities smarter and sustainable. Accordingly, survey data were collected from 115 respondents to evaluate the applicability of the implemented CBR recommender system in relation to how the system provides best practice recommendations and retaining of smart city initiatives. Results from descriptive and exploratory factor analyses suggest that the developed system is applicable in supporting smart city adoption. Besides, findings from this study are expected to provide valuable insights for practitioners to develop more practical strategies and for researchers to better understand smart city dimensions. (shrink)

Although many information system ontologies (ISOs) claim to be parsimonious, the notion of parsimony seems to influence the debate on ISOs only at the level of vague and uncritical assumption. To challenge this trend, the paper aims to clarify what it means for ISOs to be parsimonious. Specifically, section 2 shows that parsimony in computer science generally concerns software design and, together with elegance, is one of the two aspects of the broader notion of simplicity. Section 3 transforms the main (...) claims of parsimony in software design into claims about the content of ISOs, the combination of which is hereafter called “parsimony of content”—where “content” refers only to the content of ISOs. Sections 4-7 discuss the application of this parsimony to the design of ISOs, and outline different kinds (and combinations) of parsimony of content. Finally, section 8 considers whether parsimony of content could provide some criteria both for selecting and/or classifying the contents of ISOs and for choosing between different and equally consistent ISOs. (shrink)

YouTube has been implicated in the transformation of users into extremists and conspiracy theorists. The alleged mechanism for this radicalizing process is YouTube’s recommender system, which is optimized to amplify and promote clips that users are likely to watch through to the end. YouTube optimizes for watch-through for economic reasons: people who watch a video through to the end are likely to then watch the next recommended video as well, which means that more advertisements can be served to them. (...) This is a seemingly innocuous design choice, but it has a troubling side-effect. Critics of YouTube have alleged that the recommender system tends to recommend extremist content and conspiracy theories, as such videos are especially likely to capture and keep users’ attention. To date, the problem of radicalization via the YouTube recommender system has been a matter of speculation. The current study represents the first systematic, pre-registered attempt to establish whether and to what extent the recommender system tends to promote such content. We begin by contextualizing our study in the framework of technological seduction. Next, we explain our methodology. After that, we present our results, which are consistent with the radicalization hypothesis. Finally, we discuss our findings, as well as directions for future research and recommendations for users, industry, and policy-makers. (shrink)

In the contemporary digital age, recommender systems (RSs) play a fundamental role in managing information on online platforms: from social media to e-commerce, from travels to cultural consumptions, automated recommendations influence the everyday choices of users at an unprecedented scale. RSs are trained on users’ data to make targeted suggestions to individuals according to their expected preference, but their ultimate impact concerns all the multiple stakeholders involved in the recommendation process. Therefore, whilst RSs are useful to reduce information (...) overload, their deployment comes with significant ethical challenges, which are still largely unaddressed because of proprietary constraints and regulatory gaps that limit the effects of standard approaches to explainability and transparency. In this context, I address the ethical and social implications of automated recommendations by proposing a pro-ethical design framework aimed at reorienting the influence of RSs towards societal interest. In particular, after highlighting the problem of explanation for RSs, I discuss the application of beneficent informational nudging to the case of conversational recommender systems (CRSs), which rely on user-system dialogic interactions. Subsequently, through a comparison with standard recommendations, I outline the incentives for platforms and providers in adopting this approach and its benefits for both individual users and society. (shrink)

Feasting on a plethora of social media platforms, news aggregators, and online marketplaces, recommender systems (RSs) are spreading pervasively throughout our daily online activities. Over the years, a host of ethical issues have been associated with the diffusion of RSs and the tracking and monitoring of users’ data. Here, we focus on the impact RSs may have on personal autonomy as the most elusive among the often-cited sources of grievance and public outcry. On the grounds of a philosophically (...) nuanced notion of autonomy, we illustrate three specific reasons why RSs may limit or compromise it: the threat of manipulation and deception associated with RSs; the RSs’ power to reshape users’ personal identity; the impact of RSs on knowledge and critical thinking. In our view, however, notwithstanding these legitimate concerns, RSs may effectively help users to navigate an otherwise overwhelming landscape. Our perspective, therefore, is not to be intended as a bulwark to protect the _status quo_ but as an invitation to carefully weigh these aspects in the design of ethically oriented RSs. (shrink)

In the domain of information systems ontologies, the notion of completeness refers to ontological contents by demanding that they be exhaustive with respect to the domain that the ontology aims to represent. The purpose of this paper is to analyze such a notion, by distinguishing different varieties of completeness and by questioning its consistency with the open-world assumption, which formally assumes the incompleteness of conceptualizations on information systems ontologies.

Recommender systems are recently developed computer-assisted tools that support social and informational needs of various communities and help users exploit huge amounts of data for making optimal decisions. In this study, we present a new recommender system for assessment and risk prediction in child welfare institutions in Israel. The system exploits a large diachronic repository of manually completed questionnaires on functioning of welfare institutions and proposes two different rule-based computational models. The system accepts users’ requests via a (...) simple graphical interface, calculates the institutions’ profiles according to user preferences, and presents assessment scores, trends and comparative analyses of the corresponding data using assorted visual aids. Based on the analysis, the system offers three different strategies for objective assessment of the institutions’ functioning and risks. Qualitative and quantitative evaluation of the system’s effectiveness and accuracy demonstrates that it substantially improves the assessment process of a welfare institution. Moreover, it provides an effective tool for objective large-scale analysis of the institution’s overall state and trends, which were previously based primarily on the institution supervisors’ subjective judgment and intuition. In addition, the proposed recommender system has great practical and social impact as it may help identify and avert potential problems, malfunctions, flaws, risks and even tragic incidents in child welfare institutions, as well as increase their overall functioning levels. As a result, as a long-term social implication, the system may also help reduce inequality and social gaps in the Israeli society. (shrink)

Recommendation systems (RSs) predict what the user likes and recommend it to them. While at the onset of RSs, the latter was designed to maximize the recommendation accuracy (i.e., accuracy was their only goal), nowadays many RSs models include diversity in recommendations (which thus is a further goal of RSs). In the computer science community, the introduction of diversity in RSs is justified mainly through economic reasons: diversity increases user satisfaction and, in niche markets, profits.I contend that, first, the (...) economic justification of diversity in RSs risks reducing it to an empirical matter of preference; second, diversity is ethically relevant as it supports two autonomy rights of the user: the right to an open present and the right to be treated as an individual. So far, diversity in RSs has been morally defended only in the case of RSs of news and scholarly content: diversity is held to have a depolarizing effect in a democratic society and the scientific community and make the users more autonomous in their news choices. I provide a justification of diversity in RSs that embraces all kinds of RSs (i.e., a holistic moral defense) and is based on a normative principle founded on the agency of the user, which I call the right to be an exception to predictions. Such a right holds that the proper treatment of a RS user qua agent forbids providing them with recommendations based only on their past or similar users’ choices. (shrink)

The purpose is to provide researchers with reliable Scientific Research Data from the massive amounts of research data to establish a sustainable Scientific Research environment. Specifically, the present work proposes establishing an Intelligent Recommendation System based on Machine Learning algorithm and SRD. Firstly, the IRS is established over ML technology. Then, based on user Psychology and Collaborative Filtering recommendation algorithm, a hybrid algorithm [namely, Content-Based Recommendation-Collaborative Filtering ] is established to improve the utilization efficiency of SRD and Sustainable Development of (...) SR. Consequently, the present work designs literature and SRD-targeted IRS using the hybrid recommendation under the background of SD. The proposed system’s feasibility is analyzed through experiments. Additionally, the system performance is analyzed and verified from accuracy, diversity, coverage, novelty, and recommendation efficiency. The results show that the hybrid algorithm can make up for the shortcomings of a single algorithm and improve the recommendation efficiency. Experiments show that the accuracy of the proposed CBR-CF algorithm is the highest. In particular, the recommendation accuracy for the single-user system can reach 82–93%, and the recall of all recommended algorithms falls between 60 and 91%. The recall of the hybrid algorithm is higher than that of a single algorithm, and the highest recall is 91%. Meanwhile, the hybrid algorithm has comprehensive coverage, good applicability, and diversity. Therefore, SD-oriented SRD-targeted IRS is of great significance to improve the SRD utilization and the accuracy of IRS, and expand the achievement value of SR. The research content provides a reference for establishing a sustainable SR environment and improving SR efficiency. (shrink)

Insofar as disagreement may in principle regard most of (maybe all) facets of information system ontologies’ [ISOs] debate, it may also produce a plurality of views – sometimes inconsistent with each other – on ISOs’ development and design. This paper analyzes a view that makes the recognition of – and provides a theoretical foundation for – such a plurality of views a trademark: perspectivism (on ISOs). The aim is to show what exactly endorsing perspectivism consists of, and how perspectivism differs (...) from different, competing views. Section 2 introduces the main claims of perspectivism, and remarks that perspectivism mainly deals with ISOs’ development and design. As for ISOs’ development, Sect. 3 considers domain’s partition and systematization, by distinguishing perspectivism from realism and relativism. Section 3 also shows that perspectivism implies some sort of variantism on ISOs’ representational primitives, about which perspectivism may not differ from its rivals. As for the ISOs’ design, Sect. 4 points out that despite perspectivism grants the possibility to use any procedural approach, principle, and ontological language, it is not committed to uphold that all those approaches, principles, and languages are legitimate. Finally, Sect. 5 focuses on both perspectivism’s weaknesses and (theoretical) contribution to ISOs’ debate. (shrink)

The current (still limited) use of the notion of informativeness in the domain of information system ontologies seems to indicate that such ontologies are informative if and only if they are understandable for their final recipients. This paper aims at discussing some theoretical issues emerging from that use which, as we will see, connects the informativeness of information system ontologies to their representational primitives, domains of knowledge, and final recipients. Firstly, we maintain that informativeness interacts not only with the actual (...) representational primitives, but also with their variability over time. Secondly, we discuss the correspondence between representational primitives and domains of knowledge of those ontologies. Finally, we explore the possibility of an epistemological discrepancy between human beings and software systems on the understanding of ontological contents. (shrink)

There are many studies conducted on recommendation systems, most of which are focused on recommending items to users and vice versa. Nowadays, social networks are complicated due to carrying vast arrays of data about individuals and organizations. In today’s competitive environment, companies face two significant problems: supplying resources and attracting new customers. Even the concept of supply-chain management in a virtual environment is changed. In this article, we propose a new and innovative combination approach to recommend organizational people in (...) social networks based on organizational communication and SCM. The proposed approach uses a hybrid strategy that combines basic collaborative filtering and demographic recommendation systems, using data mining, artificial neural networks, and fuzzy techniques. The results of experiments and evaluations based on a real dataset collected from the LinkedIn social network showed that the hybrid recommendation system has higher accuracy and speed than other essential methods, even substantially has eliminated the fundamental problems with such systems, such as cold start, scalability, diversity, and serendipity. (shrink)

A personalized recommender system is broadly accepted as a helpful tool to handle the information overload issue while recommending a related piece of information. This work proposes a hybrid personalized recommender system based on affinity propagation, namely, APHPRS. Affinity propagation is a semisupervised machine learning algorithm used to cluster items based on similarities among them. In our approach, we first calculate the cluster quality and density and then combine their outputs to generate a new ranking score among clusters (...) for the personalized recommendation. In the first phase, user preferences are collected and normalized as items rating matrix. This generated matrix is then clustered offline using affinity propagation and kept in a database for future recommendations. In the second phase, online recommendations are generated by applying the offline model. Negative Euclidian similarity and the quality of clusters are used together to select the best clusters for recommendations. The proposed APHPRS system alleviates problems such as sparsity and cold-start problems. The use of affinity propagation and the hybrid recommendation technique used in the proposed approach helps in improving results against sparsity. Experiments reveal that the proposed APHPRS performs better than most of the existing recommender systems. (shrink)

This paper is a methodological and theoretical meditation on how some research has approached the question of the evolution of human cognitive traits. I discuss views that explicitly or implicitly endorse a view of human cognition as originating from a cause that can be singled out. Following Ross and Ladyman (2010), I suggest that this “singling-out” strategy correlates with a “container” metaphor that doesn’t fit with the interactive process-ontology of modern physics (Campbell 2009). Instead, Ross and Ladyman as well (...) as Campbell recommend the metaphor of ‘emergence’. The logic and ontology of emergent systems finds resonance with developmental systems theory in biology. I suggest in agreement with Stotz (Phenomenology and the Cognitive Sciences 9(4), 2010) that we view the origins of human mindedness within such a framework. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Anthropological Perspectives in Psychiatric NosologyJuan J. López-Ibor Jr. (bio) and María-Inés López-Ibor (bio)KeywordsDSM, etiology, Aristotelian causes, social dramasPsychiatry and clinical psychology, as we learn in this paper, are disciplines in need of an ontological perspective. Very few branches of contemporary learning share this characteristic. Probably only theoretical physic and theology—as the rest have long ago given up trying to define and understand the essence of their object, for example, (...) life in the case of biology or mind in psychology. Consequently, the paper by Pérez-Álvarez, Sass and García-Montes, “The Ontology of Mental Disorders in Constructivist Perspective,” (2008) should be welcomed and indeed included in the reading lists for trainees in psychiatry and clinical psychology.The authors propose an approach to the understanding of mental disorders that is extremely attractive and well articulated, and which also has practical implications for clinicians. It is not just another “philosophical divertimento” devoid of scientific and practical importance. Let us analyze the article in an orderly way.Less DsmThe authors of the target paper disapprove of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-III/IV approach to defining illnesses by starting from the symptoms that are present—on the grounds that this may lead clinicians to assume that their sole role is to identify, fight, and suppress the symptoms by whichever procedure. They propose an alternative that is dear to myself because it follows the path of the so-called “anthropological” psychiatry of Binswanger, von Gebsattel, Erwin Strauss, Zutt, López-Ibor, Sr., and others. In essence, this is a phenomenological approach to the meaning of mental diseases, one that emphasizes how the illness is revealed to the patient him- or herself.The target article’s criticism of DSM should be considered in the context of the abuses committed on its behalf. The DSM is not a textbook of psychiatric disorders, nor does it contain a definition of the diseases. The DSM does not tell what a disease is (Klerman et al. 1984)—something that is impossible with a classification system based on the manifestations of the diseases, the signs and symptoms. The DSM, as its title states, is just a diagnostic and statistical manual, which does not contain anything about the origin of [End Page 259] any disease nor an explanation of why it exists or what it means. The DSM is, in fact, just a tool to determine whether a disease is present, and therefore to facilitate communication between professionals and with other individuals, without saying anything about the disease’s aitia—a key term (associated with notions of essence as well as cause) to be discussed below. In theory, most clinicians should understand these limitations; it may be, however, that this is not really the case for many who read or use the DSM. In the world there are around 200,000 psychiatrists; since 1980 the number of DSM copies sold is in the order of several hundred thousand.The misuse of a classification system is even more noticeable in the International Classification of Diseases (ICD)-10 Research Version. The instructions for the use of this version recommend that the first step is to make an inventory of all the symptoms present, and then to construct a diagnosis based on them. This how all computer-assisted systems work. This procedure can, however, only be valid if the clinician has already reached a diagnostic conclusion by other means—a diagnosis then to be confirmed for research purposes. It may be that this is one of the reasons why the ICD-10 Research Version has almost never actually been used for research.Furthermore, the concept of symptoms in psychiatry applies only to organic mental disorders (Schneider 1959), conditions in which the patient’s attitude and way of experiencing the symptoms do not play the kind of role that they play in schizophrenia and other mental disorders. The quotation from the important paper by Sass and Parnas in this context is most appropriate. It is indeed that case that “subjective experience can play an important causal role in the progressive experiential transformations of a developing schizophrenic illness... (shrink)