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)

It is relatively easy to state that information retrieval is a scientific discipline but it is rather difficult to understand why it is science because what is science is still under debate in the philosophy of science. To be able to convince others that IR is science, our ability to explain why is crucial. To explain why IR is a scientific discipline, we use a theory and a model of scientific study, which were proposed recently. The explanation involves (...) mapping the knowledge structure of IR to that of well-known scientific disciplines like physics. In addition, the explanation involves identifying the common aim, principles and assumptions in IR and in well-known scientific disciplines like physics, so that they constrain the scientific investigation in IR in a similar way as in physics. Therefore, there are strong similarities in terms of the knowledge structure and the constraints of the scientific investigations between IR and scientific disciplines like physics. Based on such similarities, IR is considered a scientific discipline. (shrink)

The effectiveness of information retrieval technology in electronic discovery (E-discovery) has become the subject of judicial rulings and practitioner controversy. The scale and nature of E-discovery tasks, however, has pushed traditional information retrieval evaluation approaches to their limits. This paper reviews the legal and operational context of E-discovery and the approaches to evaluating search technology that have evolved in the research community. It then describes a multi-year effort carried out as part of the Text Retrieval (...) Conference to develop evaluation methods for responsive review tasks in E-discovery. This work has led to new approaches to measuring effectiveness in both batch and interactive frameworks, large data sets, and some surprising results for the recall and precision of Boolean and statistical information retrieval methods. The paper concludes by offering some thoughts about future research in both the legal and technical communities toward the goal of reliable, effective use of information retrieval in E-discovery. (shrink)

A variety of legal documents are increasingly being made available in electronic format. Automatic Information Search and Retrieval algorithms play a key role in enabling efficient access to such digitized documents. Although keyword-based search is the traditional method used for text retrieval, they perform poorly when literal term matching is done for query processing, due to synonymy and ambivalence of words. To overcome these drawbacks, an ontological framework to enhance the user’s query for retrieval of truly (...) relevant legal judgments has been proposed in this paper. Ontologies ensure efficient retrieval by enabling inferences based on domain knowledge, which is gathered during the construction of the knowledge base. Empirical results demonstrate that ontology-based searches generate significantly better results than traditional search methods. (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 (...) class='Hi'>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)

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)

In this paper we take a fresh look at the information retrieval problem of balancing recall with precision in electronic document extraction. We examine the IR constructs of uncertainty, context and relevance, proposing a new process model for context learning, and introducing a new IT artifact designed to support user driven learning by leveraging explicit knowledge to discover implicit knowledge within a corpus of documents. The IT artifact is a prototype designed to present a small set of extracted (...) documents from a targeted corpus based upon user inputted criteria. The prototype provides the user with the opportunity to balance exploration and exploitation, via iterative relevance feedback to address the problem of imprecision resulting from uncertainty. We model the problem as an exploration–exploitation dilemma and apply it to a specific case of IR called eDiscovery. We conduct a series of behavioral experiments to evaluate the model and the artifact. Our initial findings indicate that the proposed model and the artifact improve performance in the IR result. (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)

This paper proposes an agent community based information retrieval method, which uses agent communities to manage and look up information related to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. In order to retrieve information related to a user query, an agent uses two histories : a query/retrieved document (...) history(Q/RDH) and a query/sender agent history(Q/SAH). The former is a list of pairs of a query and retrieved documents, where the queries were sent by the agent itself. The latter is a list of pairs of a query and sender agents and shows ``who sent what query to the agent''. This is useful to find a new information source. Making use of the Q/SAH is expected to cause a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads to perform a search. As an agent receives more queries, then more links to new knowledge are achieved. From this behavior, a ``give and take''(or positive feedback) effect for agents seems to emerge. We implemented this method with Multi-Agents Kodama which has been developed in our laboratory, and conducted preliminary experiments to test the hypothesis. The empirical results showed that the method was much more efficient than a naive method employing 'broadcast' techniques only to look up a target agent. (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)

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)

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.

The main object of the paper is to demonstrate in detail the role of classification in information retrieval (IR) and the design of classificatory structures by the application of logical division to all forms of the content of records, subject and imaginative. The natural product of such division is a faceted classification. The latter is seen not as a particular kind of library classification but the only viable form enabling the locating and relating of information to be (...) optimally predictable. A detailed exposition of the practical steps in facet analysis is given, drawing on the experience of the new Bliss Classification (BC2). The continued existence of the library as a highly organized information store is assumed. But, it is argued, it must acknowledge the relevance of the revolution in library classification that has taken place. It considers also how alphabetically arranged subject indexes may utilize controlled use of categorical (generically inclusive) and syntactic relations to produce similarly predictable locating and relating systems for IR. (shrink)

Some studies have reported that, under some circumstances, participants sometimes reject the truth of conditional premises and give incorrect uncertain conclusions to MP and MT, despite the standard instructions to assume the truth of the premises. Instructions that emphasise the logical nature of the task, on the other hand, increase the number of valid conclusions to these two inferences. In this paper, we examine two possible explanations for the influence of instructions on the production of valid conclusions: (1) instructions trigger (...) a logical mode of thinking that is appropriate for the task to be solved, and (2) instructions affect the way that retrieved information is used when constructing a mental representation of the premises. In order to compare these two hypothesis, we used conditional causal relations having either many or few disabling conditions (i.e. cases of P and not-Q) and presented them in four different instructional conditions. When presented with the standard instructions to suppose the premises to be true, MP and MT inferences show a relatively low percentage of valid conclusions. However, when the logical nature of the task and the necessity to assume the truth of the premises are emphasised, the number of valid conclusions greatly increases. Also, if disabling conditions are made explicit or generated before the presentation of these logical instructions, the performance on MP and MT is lower than when only the logical instructions are presented. Finally, the instructions had no effect on AC and DA. From these results, we concluded that the instructions had an effect on the use of retrieved information rather than on inducing different modes of thinking. (shrink)

In this work, we provide a broad overview of the distinct stages of E-Discovery. We portray them as an interconnected, often complex workflow process, while relating them to the general Electronic Discovery Reference Model (EDRM). We start with the definition of E-Discovery. We then describe the very positive role that NIST’s Text REtrieval Conference (TREC) has added to the science of E-Discovery, in terms of the tasks involved and the evaluation of the legal discovery work performed. Given the critical (...) nature that data analysis plays at various stages of the process, we present a pyramid model, which complements the EDRM model: for gathering and hosting; indexing; searching and navigating; and finally consolidating and summarizing E-Discovery findings. Next we discuss where the current areas of need and areas of growth appear to be, using one of the field’s most authoritative surveys of providers and consumers of E-Discovery products and services. We subsequently address some areas of Artificial Intelligence, both Information Retrieval-related and not, which promise to make future contributions to the E-Discovery discipline. Some of these areas include data mining applied to e-mail and social networks, classification and machine learning, and the technologies that will enable next generation E-Discovery. The lesson we convey is that the more IR researchers and others understand the broader context of E-Discovery, including the stages that occur before and after primary search, the greater will be the prospects for broader solutions, creative optimizations and synergies yet to be tapped. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to (...) preserve privacy. Previously, we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)

A total of 152 students were asked to respond to a series of causal conditional (“If P then Q”) inferences with major premises for which there was variable access to information contradicting the premises. Half the students were given 12.5 s for each inference, the other half were given 8.5 s. The percentage of accepted inferences was significantly lower when the time was shorter for the MP and MT inferences, but no effect was observed for the AC and DA (...) inferences. Results are interpreted as supporting the idea that inhibition of retrieved information contradicting the premise is necessary to explain reasoning with the MP and MT inferences under logical instructions (Markovits & Barrouillet, 2002). (shrink)

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)

Selective retrieval of task-relevant information often facilitates memory retention of that information. However, it is still unclear if selective retrieval of task-relevant information can alter memory for task-irrelevant information, and the role of emotional arousal in it. In two experiments, we used emotional and neutral faces as stimuli, and participants were asked to memorise the name (who is this person?) and location (where does he/she come from?) associated with each face in initial study. Then, (...) half of the studied faces were presented as cues, and participants were asked to retrieve the corresponding names (Experiment 1) or locations (Experiment 2). Finally, all the faces were presented and participants were asked to retrieve both the corresponding names and locations. The results of the final test showed that retrieval practice not only enhanced memory of task-relevant information but also enhanced memory of task-irrelevant information. More importantly, negative emotion amplified the retrieval practice effect overall, with a larger retrieval-induced benefit for the negative than neutral condition. These findings demonstrated an emotional arousal amplification effect on retrieval-induced enhancement effects, suggesting that the advantage of the retrieved memory representations can be amplified by emotional arousal even without explicit goals in a task setting. (shrink)

In this study, we intend to examine information retrieval behaviors from a psychological point of view using a search engine on the World Wide Web (WWW). We investigated information retrieving behaviors in detail based on both the recorded data of retrievers’ web browsing actions and their thinking processes by the “think aloud” method. We focused on selected keywords for retrieving and compared them between retrievers who had enough knowledge about their task and those who did not. Our (...) goal was to learn about the literacy needed for finding required information efficiently on the WWW. (shrink)