In patent prosecution, timely and effective responses to Office Actions (OAs) are crucial for securing patents. However, past automation and artificial intelligence research have largely overlooked this aspect. To bridge this gap, our study introduces the Patent Office Action Response Intelligence System (PARIS) and its advanced version, the Large Language Model (LLM) Enhanced PARIS (LE-PARIS). These systems are designed to enhance the efficiency of patent attorneys in handling OA responses through collaboration with AI. The systems’ key features include the (...) construction of an OA Topics Database, development of Response Templates, and implementation of Recommender Systems and LLM-based Response Generation. To validate the effectiveness of the systems, we have employed a multi-paradigm analysis using the USPTO Office Action database and longitudinal data based on attorney interactions with our systems over six years. Through five studies, we have examined the constructiveness of OA topics (studies 1 and 2) using topic modeling and our proposed Delphi process, the efficacy of our proposed hybrid LLM-based recommender system tailored for OA responses (study 3), the quality of generated responses (study 4), and the systems’ practical value in real-world scenarios through user studies (study 5). The results indicate that both PARIS and LE-PARIS significantly achieve key metrics and have a positive impact on attorney performance. (shrink)

Retrieval of relevant unstructured information from the ever-increasing textual communications of individuals and businesses has become a major barrier to effective litigation/defense, mergers/acquisitions, and regulatory compliance. Such e-discovery requires simultaneously high precision with high recall (high-P/R) and is therefore a prototype for many legal reasoning tasks. The requisite exhaustive information retrieval (IR) system must employ very different techniques than those applicable in the hyper-precise, consumer search task where insignificant recall is the accepted norm. We apply (...) Russell, et al.’s cognitive task analysis of sensemaking by intelligence analysts to develop a semi-autonomous system that achieves high IR accuracy of F1 ≥ 0.8 compared to F1 < 0.4 typical of computer-assisted human-assessment (CAHA) or alternative approaches such as Roitblat, et al.’s. By understanding the ‘Learning Loop Complexes’ of lawyers engaged in successful small-scale document review, we have used socio-technical design principles to create roles, processes, and technologies for scalable human-assisted computer-assessment (HACA). Results from the NIST-TREC Legal Track’s interactive task from both 2008 and 2009 validate the efficacy of this sensemaking approach to the high-P/R IR task. (shrink)

Automated classification of legal documents has been the subject of extensive research in recent years. However, this is still a challenging task for long documents, since it is difficult for a model to identify the most relevant information for classification. In this paper, we propose a two-stage supervised learning approach for the classification of petitions, a type of legal document that requests a court order. The proposed approach is based on a word-level encoder–decoder Seq2Seq deep neural network, such (...) as a Bidirectional Long Short-Term Memory (BiLSTM) or a Bidirectional Encoder Representations from Transformers (BERT) model, and a document-level Support Vector Machine classifier. To address the challenges posed by the lengthy legal documents, the approach introduces a human-in-the-loop approach, whose task is to localize and tag relevant segments of text in the word-level training part, which dramatically reduces the dimension of the document classifier input vector. We performed experiments to validate our approach using a real-world dataset comprised of 270 intermediate petitions, which were carefully annotated by specialists from the 15th civil unit of the State of Alagoas, Brazil. Our results revealed that both BiLSTM and BERT-Convolutional Neural Networks variants achieved an accuracy of up to 95.49%, and also outperformed baseline classifiers based on the Term Frequency–Inverse Document Frequency test vectorizer. The proposed approach is currently being utilized to automate the aforementioned justice unit, thereby increasing its efficiency in handling repetitive tasks. (shrink)

Recently, the pandemic caused by COVID-19 is severe in the entire world. The prevention and control of crimes associated with COVID-19 are critical for controlling the pandemic. Therefore, to provide efficient and convenient intelligent legal knowledge services during the pandemic, we develop an intelligent system for legal information retrieval on the WeChat platform in this paper. The data source we used for training our system is “The typical cases of national procuratorial authorities handling crimes against the (...) prevention and control of the new coronary pneumonia pandemic following the law”, which is published online by the Supreme People’s Procuratorate of the People’s Republic of China. We base our system on convolutional neural network and use the semantic matching mechanism to capture inter-sentence relationship information and make a prediction. Moreover, we introduce an auxiliary learning process to help the network better distinguish the relation between two sentences. Finally, the system uses the trained model to identify the information entered by a user and responds to the user with a reference case similar to the query case and gives the reference legal gist applicable to the query case. (shrink)

Information Retrieval systems benefit from the use of long queries containing a large volume of search-relevant information. This situation is not common, as users of such systems tend to use very short and precise queries with few keywords. In this work we propose a modification of the Latent Dirichlet Allocation (LDA) technique using data from the document collection and its vocabulary for a better representation of short queries. Additionally, a study is carried out on how the modification (...) of the proposed LDA weighted vectors increase the performance using relevant documents as feedback. The work shown in this paper is tested using three biomedical corpora (TREC Genomics 2004, TREC Genomics 2005 and OHSUMED) and one legal corpus (FIRE 2017). Results prove that the application of the proposed representation technique, as well as the feedback adjustment, clearly outperforms the baseline methods (BM25 and non-modified LDA). (shrink)

Text classification involves deciding whether or not a document is about a given topic. It is an important problem in machine learning, because automated text classifiers have enormous potential for application in information retrieval systems. It is also an interesting problem for cognitive science, because it involves real world human decision making with complicated stimuli. This paper develops two models of human text document classification based on random walk and accumulator sequential sampling processes. The models are evaluated (...) using data from an experiment where participants classify text documents presented one word at a time under task instructions that emphasize either speed or accuracy, and rate their confidence in their decisions. Fitting the random walk and accumulator models to these data shows that the accumulator provides a better account of the decisions made, and a “balance of evidence” measure provides the best account of confidence. Both models are also evaluated in the applied information retrieval context, by comparing their performance to established machine learning techniques on the standard Reuters‐21578 corpus. It is found that they are almost as accurate as the benchmarks, and make decisions much more quickly because they only need to examine a small proportion of the words in the document. In addition, the ability of the accumulator model to produce useful confidence measures is shown to have application in prioritizing the results of classification decisions. (shrink)

Access to legal information and, in particular, to legal literature is examined for the creation of a search and retrieval system for Italian legal literature. The design and implementation of services such as integrated access to a wide range of resources are described, with a particular focus on the importance of exploiting metadata assigned to disparate legal material. The integration of structured repositories and Web documents is the main purpose of the system: it is constructed on (...) the basis of a federation system with service provider functions, aiming at creating a centralized index of legal resources. The index is based on a uniform metadata view created for structured data by means of the OAI approach and for Web documents by a machine learning approach, which, in this paper, has been assessed as regards document classification. Semantic searching is a major requirement for legal literature users and a solution based on the exploitation of Dublin Core metadata, as well as the use of legal ontologies and related terms prepared for accessing indexed articles have been implemented. (shrink)

The field of computational law has increasingly moved into the focus of the scientific community, with recent research analysing its issues and risks. In this article, we seek to draw a structured and comprehensive list of societal issues that the deployment of automatically processable regulation could entail. We do this by systematically exploring attributes of the law that are being challenged through its encoding and by taking stock of what issues current projects in this field raise. This article adds to (...) the current literature not only by providing a needed framework to structure arising issues of computational law but also by bridging the gap between theoretical literature and practical implementation. Key findings of this article are: (1) The primary benefit (efficiency vs. accessibility) sought after when encoding law matters with respect to the issues such an endeavor triggers; (2) Specific characteristics of a project—project type, degree of mediation by computers, and potential for divergence of interests—each impact the overall number of societal issues arising from the implementation of automatically processable regulation. (shrink)

Web legal information retrieval systems need the capability to reason with the knowledge modeled by legal ontologies. Using this knowledge it is possible to represent and to make inferences about the semantic content of legal documents. In this paper a methodology for applying NLP techniques to automatically create a legal ontology is proposed. The ontology is defined in the OWL semantic web language and it is used in a logic programming framework, EVOLP+ISCO, to allow users to query the (...) semantic content of the documents. ISCO allows an easy and efficient integration of declarative, object-oriented and constraint-based programming techniques with the capability to create connections with external databases. EVOLP is a dynamic logic programming framework allowing the definition of rules for actions and events. An application of the proposed methodology to the legal web information retrieval system of the Portuguese Attorney General’s Office is described. (shrink)

An application of Narrative Knowledge Representation Language (NKRL) techniques on (declassified) ‘terrorism in Southern Philippines’ documents has been carried out in the context of the IST Parmenides project. This paper describes some aspects of this work: it is our belief, in fact, that the Knowledge Representation techniques and the Intelligent Information Retrieval tools used in this experiment can be of some interest also in an ‘Ontological Modelling of Legal Events and Legal Reasoning’ context.

Automated Vehicles (AVs) are designed and programmed to follow traffic rules. However, there is no separate and comprehensive regulatory framework dedicated to AVs. The current Queensland traffic rules were designed for humans. These rules often contain open texture expressions, exceptions, and potential conflicts (conflict arises when exceptions cannot be handled in rules), which makes it hard for AVs to follow. This paper presents an automatic compliance checking framework to assess AVs behaviour against current traffic rules by addressing these issues. (...) Specifically, it proposes a framework to determine which traffic rules and open texture expressions need some additional interpretation. Essentially this enables AVs to have a suitable and executable formalization of the traffic rules. Defeasible Deontic Logic (DDL) is used to formalize traffic rules and reasoning with AV information (behaviour and environment). The representation of rules in DDL helps effectively in handling and resolving exceptions, potential conflicts, and open textures in rules. 40 experiments were conducted on eight realistic traffic scenarios to evaluate the framework. The evaluation was undertaken both quantitatively and qualitatively. The evaluation result shows that the proposed framework is a promising system for checking Automated Vehicle interpretation and compliance with current traffic rules. (shrink)

Many countries employ systemic methods of protecting consumers from unfair business practices. One such practice is the use of abusive clauses in business-to-consumer (B2C) contracts, which unfairly impose additional obligations on the consumer or deprive them of their due rights. This article presents an information system that utilizes artificial intelligence methods to automate contract analysis and to detect abusive clauses. The goal of the system is to support the entire administrative process, from contract acquisition, through text extraction (...) and the recommendation of potentially abusive clauses, to the generation of official administrative documents that can be sent to court or to the owners of firms. This article focuses on the components that use machine learning methods. The first is an intelligent crawler that is responsible for automatically detecting contract templates on websites and retrieving them into the system. The second is a document analysis module that implements a clause recommendation algorithm. The algorithm employs transformer-based language models and information retrieval methods to identify abusive passages in text. Our solution achieved first place in a competition on the automatic analysis of B2C contracts organized by the Polish Office of Competition and Consumer Protection (UOKiK), and has since been implemented as an official tool to support the contract analysis process in Poland. (shrink)

The International workshop 'Frontiers of Combining Systems' is the only forum that is exclusively devoted to research efforts in this interdisciplinary area. This volume contains selected, edited papers from the second installment of the workshop. The contributions range from theorem proving, rewriting and logic to systems and constraints. While there is a clear emphasis on automated tools and logics, the contributions to this volume show that there exists a rapidly expanding body of solutions of particular instances of the combination (...) problem, and at the same time, that the issue of developing general frameworks for intergrating formalisms and systems is taking on an increasingly important position on the international research agenda. The idea of combining formal systems and algorithms has been attracting interest in areas as diverse as constraint logic programming, automated deduction, verification, information retrieval, computational linguistics, artificial intelligence, and logic. As any interesting real world system is a complex composite entity, decomposing its descriptive requirements (for design, verification, or maintenance purposes) into simpler, more restricted tasks is appealing as it is often the only plausible way of tackling complex modelling problems. A core body of notions, questions and results is beginning to emerge in the area, and we are beginning to understand the computational and logical impact of combining methods and algorithms. (shrink)

In this work we study, design, and evaluate computational methods to support interpretation of statutory terms. We propose a novel task of discovering sentences for argumentation about the meaning of statutory terms. The task models the analysis of past treatment of statutory terms, an exercise lawyers routinely perform using a combination of manual and computational approaches. We treat the discovery of sentences as a special case of ad hoc document retrieval. The specifics include retrieval of short texts, specialized (...) document types, and, above all, the unique definition of document relevance provided in detailed annotation guidelines. To support our experiments we assembled a data set comprising 42 queries which we plan to release to the public in the near future in order to support further research. Most importantly, we investigate the feasibility of developing a system that responds to a query with a list of sentences that mention the term in a way that is useful for understanding and elaborating its meaning. This is accomplished by a systematic assessment of different features that model the sentences’ usefulness for interpretation. We combine features into a compound measure that accounts for multiple aspects. The definition of the task, the assembly of the data set, and the detailed task analysis provide a solid foundation for employing a learning-to-rank approach. (shrink)

_Introduction:_ Clinically relevant information can go uncaptured in the conventional scoring of a verbal fluency test. We hypothesize that characterizing the temporal aspects of the response through a set of time related measures will be useful in distinguishing those with MCI from cognitively intact controls. _Methods:_ Audio recordings of an animal fluency test administered to 70 demographically matched older adults (mean age 90.4 years), 28 with mild cognitive impairment (MCI) and 42 cognitively intact (CI) were professionally transcribed and fed (...) into an automatic speech recognition (ASR) system to estimate the start time of each recalled word in the response. Next, we semantically cluster participant generated animal names and through a novel set of time-based measures, we characterize the semantic search strategy of subjects in retrieving words from animal name clusters. This set of time-based features along with standard count-based features (e.g., number of correctly retrieved animal names) were then used in a machine learning algorithm trained for distinguishing those with MCI from CI controls. _Results:_ The combination of both count-based and time-based features, automatically derived from the test response, achieved 77% on AUC-ROC of the support vector machine (SVM) classifier, outperforming the model trained only on the raw test score (AUC, 65%), and well above the chance model (AUC, 50%). _Conclusion:_ This approach supports the value of introducing time-based measures to the assessment of verbal fluency in the context of this generative task differentiating subjects with MCI from those with intact cognition. (shrink)

In the digital age, the use of advanced technology is becoming a new paradigm in police work, criminal justice, and the penal system. Algorithms promise to predict delinquent behaviour, identify potentially dangerous persons, and support crime investigation. Algorithm-based applications are often deployed in this context, laying the groundwork for a ‘smart criminal justice’. In this qualitative study based on 32 interviews with criminal justice and police officials, we explore the reasons why and extent to which such a smart criminal (...) justice system has already been established in Switzerland, and the benefits perceived by users. Drawing upon this research, we address the spread, application, technical background, institutional implementation, and psychological aspects of the use of algorithms in the criminal justice system. We find that the Swiss criminal justice system is already significantly shaped by algorithms, a change motivated by political expectations and demands for efficiency. Until now, algorithms have only been used at a low level of automation and technical complexity and the levels of benefit perceived vary. This study also identifies the need for critical evaluation and research-based optimization of the implementation of advanced technology. Societal implications, as well as the legal foundations of the use of algorithms, are often insufficiently taken into account. By discussing the main challenges to and issues with algorithm use in this field, this work lays the foundation for further research and debate regarding how to guarantee that ‘smart’ criminal justice is actually carried out smartly. (shrink)

Intelligent Transportation Systems are expected to automate how parking slots are booked by trucks. The intrinsic dynamic nature of this problem, the need of explanations and the inclusion of private data justify an agent-based solution. Agents solving this problem act with a Believe Desire Intentions reasoning, and are implemented with JASON. Privacy of trucks becomes protected sharing a list of parkings ordered by preference. Furthermore, the process of assigning parking slots takes into account legal requirements on breaks and driving time (...) limits. Finally, the agent simulations use the distances, the number of trucks and parkings corresponding to the proportions of the current European Union data. The performance of the proposed solution is tested in these simulations with three different distances against an alternative with complete knowledge. The difference in efficiency, the number of illegal breaks and the traveled distances are measured in them. Comparing the results, we can conclude that the nonprivate alternative is slightly better in performance while both alternatives do not produce illegal breaks. In this way the simulations show that the proposed privacy protection does not impose a relevant handicap in efficiency. (shrink)

Considerable attention has been given to the accessibility of legal documents, such as legislation and case law, both in legal information retrieval (query formulation, search algorithms), in legal information dissemination practice (numerous examples of on-line access to formal sources of law), and in legal knowledge-based systems (by translating the contents of those documents to ready-to-use rule and case-based systems). However, within AI & law, it has hardly ever been tried to make the contents of sources of law, (...) and the relations among them, more accessible to those without a legal education. This article presents a theory about translating sources of law into information accessible to persons without a legal education. It illustrates the theory by providing two elaborated examples of such translation ventures. In the first example, formal sources of law in the domain of exchanging police information are translated into rules of thumb useful for policemen. In the second example, the goal of providing non-legal professionals with insight into legislative procedures is translated into a framework for making available sources of law through an integrated legislative calendar. Although the theory itself does not support automating the several stages described, in this article some hints are given as to what such automation would have to look like. (shrink)

1 Boolean retrieval 1 2 The term vocabulary and postings lists 19 3 Dictionaries and tolerant retrieval 49 4 Index construction 67 5 Index compression 85 6 Scoring, term weighting and the vector space model 109 7 Computing scores in a complete search system 135 8 Evaluation in information retrieval 151 9 Relevance feedback and query expansion 177 10 XML retrieval 195 11 Probabilistic information retrieval 219 12 Language models for information (...) retrieval 237 13 Text classification and Naive Bayes 253 14 Vector space classification 289 15 Support vector machines and machine learning on documents 319 16 Flat clustering 349 17 Hierarchical clustering 377 18 Matrix decompositions and latent semantic indexing 403 19 Web search basics 421 20 Web crawling and indexes 443 21 Link analysis 461.. (shrink)

This article analyses Camille Henrot’s 2013 film Grosse Fatigue in relation to the histories of hypermedia and modes of interaction with the World Wide Web. It considers the development of non-hierarchical systems for the organisation of information, and uses Grosse Fatigue to draw comparisons between the Web, the natural history museum and the archive. At stake in focusing on the way in which information is organised through hypermedia is the question of subjectivity, and this article argues that such (...) systems are made ‘user-friendly’ by appearing to accommodate intuitive processes of information retrieval, reflecting the subject back to itself as autonomous. This produces an ideology of individualism which belies the forms of heteronomy that in fact shape and structure access to information online in significant ways. At the heart of this argument is an attention to the visual, and the significance of art as an immanent mode of analysis. Through the themes of transparency and opacity, and order and chaos, the article thus proposes a defining dynamic between autonomy and automation as a model for understanding the contemporary subject. (shrink)

Starting from the virtual reality technology, the characteristics of its most suitable combination with the library are explored, so as to lay a foundation in theory and practice to promote the development of virtual reality in the library. In the concentration camp of the latest advanced technology, the relevant technologies used in the various levels of models in the smart library are extracted, and their functional principles and applications are systematically introduced; Chapter 4 builds the level of the smart library (...) information retrieval technology model. The structure diagram, various levels of functions, and related smart service models are discussed. Research is on context construction of extended resources of knowledge service in smart libraries. The elements and content of the resource context are introduced, and the strategy of constructing the resource context for the extension of the knowledge service of the smart library is proposed. Research is on the construction of the context of the extension and interconnection of knowledge services in smart libraries. The relevant elements and contents of the technical context and the spatial context are introduced, and a strategy for constructing a connected context for the extension of the knowledge service of a smart library is proposed. Research is on the context construction of knowledge service extension of smart library. The elements and contents of the service context are introduced, and the strategy of constructing the service context of the knowledge service extension of the smart library is proposed. A visual model of information retrieval is constructed. The model integrates the core steps of the information visualization process and introduces the information space and functional system in the information construction theory into it and through five mapping layers and six spatial layers, which describe visualization applications that target the user experience model in information construction build process. (shrink)

The concept of ‘relevance’ is crucial to legal information retrieval, but because of its intuitive understanding it goes undefined too easily and unexplored too often. We discuss a conceptual framework on relevance within legal information retrieval, based on a typology of relevance dimensions used within general information retrieval science, but tailored to the specific features of legal information. This framework can be used for the development and improvement of legal information retrieval (...) systems. (shrink)

Organisations increasingly use automated decision-making systems (ADMS) to inform decisions that affect humans and their environment. While the use of ADMS can improve the accuracy and efficiency of decision-making processes, it is also coupled with ethical challenges. Unfortunately, the governance mechanisms currently used to oversee human decision-making often fail when applied to ADMS. In previous work, we proposed that ethics-based auditing (EBA)—that is, a structured process by which ADMS are assessed for consistency with relevant principles or norms—can (a) help (...) organisations verify claims about their ADMS and (b) provide decision-subjects with justifications for the outputs produced by ADMS. In this article, we outline the conditions under which EBA procedures can be feasible and effective in practice. First, we argue that EBA is best understood as a ‘soft’ yet ‘formal’ governance mechanism. This implies that the main responsibility of auditors should be to spark ethical deliberation at key intervention points throughout the software development process and ensure that there is sufficient documentation to respond to potential inquiries. Second, we frame AMDS as parts of larger sociotechnical systems to demonstrate that to be feasible and effective, EBA procedures must link to intervention points that span all levels of organisational governance and all phases of the software lifecycle. The main function of EBA should, therefore, be to inform, formalise, assess, and interlink existing governance structures. Finally, we discuss the policy implications of our findings. To support the emergence of feasible and effective EBA procedures, policymakers and regulators could provide standardised reporting formats, facilitate knowledge exchange, provide guidance on how to resolve normative tensions, and create an independent body to oversee EBA of ADMS. (shrink)

The paper discusses issues related to the use of faceted classifications in an online environment. The author argues that knowledge organization systems can be fully utilized in information retrieval only if they are exposed and made available for machine processing. The experience with classification automation to date may be used to speed up and ease the conversion of existing faceted schemes or the creation of management tools for new systems. The author suggests that it is possible to agree (...) on a set of functional requirements for supporting faceted classifications online that are equally relevant for the maintenance of classifications, the creation of classification indexing tools, or the management of classifications in an authority file. It is suggested that a set of requirements for analytico-synthetic classifications may be put forward to improve standards for the use and exchange of knowledge organization systems. (shrink)

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not (...) ameliorate more general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions. (shrink)

Algorithms and automated learning systems have been successfully applied to produce images, pieces of music, or texts that are appealing to humans and that are often compared to artworks. Computational technologies are able to find surprising and original solutions–new patterns that humans cannot anticipate– but does this mean we ascribe to them the kind of creativity that is expressed by human artists? Even though AI can successfully detect humans’ preferences as well as select the objects that satisfy taste, can (...) we ascribe to them the capacity of recognizing the intrinsic value of artworks? To answer these questions, I am first going to explain the kind of creativity that is expressed by contemporary predictive systems, then, in the second part of this paper, I will try to show the difference between the creativity of algorithms and the creativity of artists by expanding on Deleuze’s reflections. (shrink)

Dutch municipalities are confronted with an increased number of prescribed environmental tasks and also with a growing demand, both from the central government and environmental pressure groups, to undertake environmental activities on their own initiative. This development over-taxed the information management of most municipalities. In the past few years, computer technology was introduced to relieve part of this pressure (e.g., by automation of registration systems). In this article we present a classification of computer applications for environmental management, investigate their (...) possible impact on the environmental knowledge and information system, and distinguish between a formal and informal knowledge domain. Special attention will be paid to expert 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)

Contemporary law offices use many different technologies for storing and retrieving documents produced in the course of legal work. This article examines two approaches in detail: document management, as exemplified by SoftSolutions, and electronic publishing, as exemplified by Folio VIEWS. Some other approaches are reviewed, and the pragmatics, politics, economics, and legalities of legal work product retrieval are discussed.

During the twentieth century, bibliographic classification theory underwent a structural revolution. The first modern bibliographic classifications were top-down systems that started at the universe of knowledge and subdivided that universe downward to minute subclasses. After the invention of faceted classification by S.R. Ranganathan, the ideal was to build bottom-up classifications that started with the universe of concepts and built upward to larger and larger faceted classes. This ideal has not been achieved, and the two kinds of classification systems are not (...) mutually exclusive. This paper examines the process by which this structural revolution was accomplished by looking at the spread of facet theory after 1924 when Ranganathan attended the School of Librarianship, London, through selected classification textbooks that were published after that date. To this end, the paper examines the role of W.C.B. Sayers as a teacher and author of three editions of The Manual of Classification for Librarians and Bibliographers. Sayers influenced both Ranganathan and the various members of the Classification Research Group (CRG) who were his students. Further, the paper contrasts the methods of evaluating classification systems that arose between Sayers’s Canons of Classification in 1915–1916 and J. Mills’s A Modern Outline of Library Classification in 1960 in order to demonstrate the speed with which one kind of classificatory structure was overtaken by another. (shrink)

Purpose Interdisciplinary linkage of information is an emerging topic to create knowledge by collaboration of experts in diverse domains. New insights can be found by using the combined techniques and information when people have the chance to discuss and communicate on a common basis. Design/methodology/approach This paper describes RMS Cloud, an information management system which allows distributed data sources to be searched using dynamic joins of results from heterogeneous data formats. It is based on the well-known (...) Mediator architecture, but reverses the connection of the data sources to grant data owners full control over the data. Findings Data owners and learners are enabled to retrieve information and to cross-connect domain-extrinsic knowledge and enhances collaborative learning with a search interface that is intuitive and easy to operate. Originality/value This novel architecture is able to connect to differently shaped data sources from interdisciplinary domains into one common retrieval interface. (shrink)

Cet article présente l'apport des sciences cognitives à l'évaluation des systèmes de recherche d'information. Correspondant à une ouverture par rapport au paradigme «système» de l'évaluation, l'approche cognitive présente néanmoins des limites à la fois théoriques et méthodologiques qui sont présentées dans la première partie. Dans la deuxième partie, une extension de l'approche cognitive, qualifiée d'approche holistique, est présentée à travers quatre modèles qui illustrent le fait que l'enjeu n'est pas seulement de comprendre le comportement des usagers afin d'améliorer la (...) performance des SRI mais consiste à offrir un modèle plus général expliquant l'interaction entre l'usager et l'information.This article addresses the benefits of the cognitive viewpoint for the evaluation of information retrieval systems. Cognitive sciences gave new opportunities regarding the restriction of the "match paradigm" but they have certain methodological and theoriterical limitations which are presented in the first part of this article. In the second part, an extension of the cognitive viewpoint, named the holistic approach, is presented using four exemples. This approach brings out a new challenge - not just to improve the systems' performances but to give an overall understanding model of the interaction between the user and the information process. (shrink)

On the basis of ecological footprint theory and tourism ecological footprint theory, the sustainable development indexes such as ecological footprint, ecological carrying capacity, ecological deficit, and ecological surplus of the research area were calculated and the long-term change pattern of each index was analyzed. This paper shows that the ecological footprint of the research area increases year by year, but the ecological footprint is always smaller than the ecological carrying capacity, indicating that the area is still in the state of (...) sustainable development. However, the per capita ecological surplus shows a decreasing trend year by year, indicating that the sustainable development of the region is getting worse. This paper proposes a reordering method of tourist attractions based on heterogeneous information fusion, and realizes the retrieval and reordering of tourist attractions based on user query and fusion of heterogeneous information, so as to help users make travel decisions. In view of the shortage of tourism commercial websites to passively provide scenic spot information, this paper puts forward a scenic spot retrieval method based on query words to enable users to obtain scenic spot information according to their needs, and constructs a tourist consumer data analysis system. The preprocessing methods and methods adopted by the data preprocessing module are analyzed in detail, and the algorithms used in the travel route analysis and consumer spending ability analysis are described in detail. The data of tourism consumers are analyzed by this system, and the results are evaluated. (shrink)

Professor Vuori's paper, first presented at the fourth Medico-legal Conference in Prague in the spring of this year, deals with the problem of the maintenance of confidentiality in computerized health records. Although more and more information is required, the hardware of the computer systems is so sophisticated that it would be very expensive indeed to 'break in' and steal from a modern data bank. Those concerned with programming computers are becoming more aware of their responsibilities concerning confidentiality and privacy, (...) to the extent that a legal code of ethics for programmers is being formulated. They are also aware that the most sensitive of all relationships--the doctor-patient relationship--could be in danger if they failed to maintain high standards of integrity. An area of danger is where administrative boundaries between systems must be crossed--say between those of health and employment. Protection of privacy must be ensured by releasing full information about the type of data being stored, and by maintaining democratic control over the establishment of information systems. (shrink)

Hypertext may represent a new paradigm capable of exploring legal sources within which links are established according to pertinent relationships found between statute texts and case law. However, to discover relevant information in such a network, a browsing mechanism is not enough when faced with a large volume of texts. This paper describes a new retrieval model where documents are represented according to both their content and relationships with other sources of information.

The exponential digitization of medical data has led to a transformation of the practice of medicine. This change notably raises a new complexity of issues surrounding health IT. The proper use of these communication tools, such as telemedicine, e-health, m-health the big medical data, should improve the quality of monitoring and care of patients for an information system to "human face". Faced with these challenges, the author analyses in an ethical angle the patient-physician relationship, sharing, transmission and storage (...) of medical information, setting pins to an ethic for the digitization of medical information. Drawing on good practice recommendations closely associated with values, this model is developing tools for reflection and present the keys to understanding the decision-making issues that reflect both the technological constraints and the complex nature of human reality in medicine. (shrink)

In a Common Law system, legal practitioners need frequent access to prior case documents that discuss relevant legal issues. Case documents are generally very lengthy, containing complex sentence structures, and reading them fully is a strenuous task even for legal practitioners. Having a concise overview of these documents can relieve legal practitioners from the task of reading the complete case statements. Legal catchphrases are (multi-word) phrases that provide a concise overview of the contents of a case document, and (...) class='Hi'>automated generation of catchphrases is a challenging problem in legal analytics. In this paper, we propose a novel supervised neural sequence tagging model for the extraction of catchphrases from legal case documents. Specifically, we show that incorporating document-specific information along with a sequence tagging model can enhance the performance of catchphrase extraction. We perform experiments over a set of Indian Supreme Court case documents, for which the gold-standard catchphrases (annotated by legal practitioners) are obtained from a popular legal information system. The performance of our proposed method is compared with that of several existing supervised and unsupervised methods, and our proposed method is empirically shown to be superior to all baselines. (shrink)

The perspective of online dispute resolution is to develop an online electronic system aimed at solving out-of-court disputes. Among ODR schemes, eMediation is becoming an important tool for encouraging the positive settlement of an agreement among litigants. The main motivation underlying the adoption of eMediation is the time/cost reduction for the resolution of disputes compared to the ordinary justice system. In the context of eMediation, a fundamental requirement that an ODR system should meet relates to both litigants (...) and mediators, i.e. to enable an informed negotiation by informing the parties about the rights and duties related to the case. In order to match this requirement, we propose an information retrieval system able to retrieve relevant court decisions with respect to the disputant case description. The proposed system combines machine learning and natural language processing techniques to better match disputant case descriptions with court decisions. Experimental results confirm the ability of the proposed solution to empower court decision retrieval, enabling therefore a well-informed eMediation process. (shrink)

The common law system is a legal system that values precedent, or previous court decisions, in the resolution of current cases. As the availability of legal documents in digital form has increased, it has become more difficult for legal professionals to manually identify relevant past cases due to the vast amount of data. Researchers have developed automated systems for determining the similarity between legal documents to address this issue. Our research explores various representations of a legal document (...) and discusses a novel paragraph filtering process to identify key paragraphs using legal citation information to remove unnecessary text paragraphs without disturbing the concept of the legal document. State-of-the-art techniques like TF-IDF, BERT, Legal Bert, Doc2Vec, and Legal-longformer are used for the performance analysis of the proposed approach with document comparison. It has been shown that a model trained on the proposed filtered paragraphs can achieve better results than a model trained on the complete text and can also shorten the document by over 40%. The proposed filtering strategy could be helpful for models like BERT, where the maximum token length is fixed. (shrink)

The article defines the algorithm and details the sequential tasks for building an effective model of automated classification of events in the information space. On the eve and during the armed aggression of the Russian Federation against Ukraine, the consequences of external negative information influence were noticeable. Therefore, the organization and implementation of counteraction to such influence is urgent. An important component of this activity is the classification of information events in the information space in (...) order to further analyze them and form proposals for decision-making to counteract the negative information impact. Given the fact that in the global information space and, in particular, the information space of the state in the interests of counteracting such influence, it is necessary to constantly process a significant amount of information, so the task of improving the efficiency of this process is provided by automating its components. The algorithm of the automated classification process is based on a number of consecutive tasks, namely: data retrieval, preelection of messages, saving pre-selected messages in the database, determining a set of indicators for automated classification of information events, pre-processing a single document, distribution of messages by criteria by categories, presentation of information in a convenient form, saving the results of classification in the database. The proposed material reveals the content of these tasks. The proposed algorithm will serve to automatically divide information events of different nature into categories in order to increase the efficiency of assessing the level of negative information impact on target audiences for timely response to its manifestations. (shrink)

This article provides an overview of, and thematic justification for, the special issue of the journal of Artificial Intelligence and Law entitled “E-Discovery”. In attempting to define a characteristic “AI & Law” approach to e-discovery, and since a central theme of AI & Law involves computationally modeling legal knowledge, reasoning and decision making, we focus on the theme of representing and reasoning with litigators’ theories or hypotheses about document relevance through a variety of techniques including machine learning. We also identify (...) two emerging techniques for enabling users’ document queries to better express the theories of relevance and connect them to documents: social network analysis and a hypothesis ontology. (shrink)