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Many existing information retrieval (IR) systems are surprisingly ineffective at finding documents relevant to particular topics. Traditional systems are extremely brittle, failing to retrieve relevant documents unless the user's exact search string is found. They support only the most primitive trial-and-error interaction with their users and are also static. Even systems with so-called "relevance feedback" are incapable of learning from experience with users. SCALIR (a Symbolic and Connectionist Approach to Legal Information Retrieval) -- a system for assisting research on copyright law -- has been designed to address these problems. By using a hybrid of symbolic and connectionist artificial intelligence techniques, SCALIR develops a conceptual representation of document relationships without explicit knowledge engineering. SCALIR's direct manipulation interface encourages users to browse through the space of documents. It then uses these browsing patterns to improve its performance by modifying its representation, resulting in a communal repository of expertise for all of its users. SCALIR's representational scheme also mirrors the hybrid nature of the Anglo-American legal system. While certain legal concepts are precise and rule-like, others -- which legal scholars call "open-textured" -- are subject to interpretation. The meaning of legal text is established through the parallel and distributed precedence-based judicial appeal system. SCALIR represents documents and terms as nodes in a network, capturing the duality of the legal system by using symbolic (semantic network) and connectionist links. The former correspond to a priori knowledge such as the fact that one case overturned another on appeal. The latter correspond to statistical inferences such as the relevance of a term describing a case. SCALIR's text corpus includes all federal cases on copyright law. The hybrid representation also suggests a way to resolve the apparent incompatibility between the two prominent paradigms in artificial intelligence, the "classical" symbol-manipulation approach and the neurally-inspired connectionist approach. Part of the book focuses on a characterization of the two paradigms and an investigation of when and how -- as in the legal research domain -- they can be effectively combined.
Book Synopsis A Symbolic and Connectionist Approach To Legal Information Retrieval by : Daniel E. Rose
Download or read book A Symbolic and Connectionist Approach To Legal Information Retrieval written by Daniel E. Rose and published by Psychology Press. This book was released on 2013-06-17 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many existing information retrieval (IR) systems are surprisingly ineffective at finding documents relevant to particular topics. Traditional systems are extremely brittle, failing to retrieve relevant documents unless the user's exact search string is found. They support only the most primitive trial-and-error interaction with their users and are also static. Even systems with so-called "relevance feedback" are incapable of learning from experience with users. SCALIR (a Symbolic and Connectionist Approach to Legal Information Retrieval) -- a system for assisting research on copyright law -- has been designed to address these problems. By using a hybrid of symbolic and connectionist artificial intelligence techniques, SCALIR develops a conceptual representation of document relationships without explicit knowledge engineering. SCALIR's direct manipulation interface encourages users to browse through the space of documents. It then uses these browsing patterns to improve its performance by modifying its representation, resulting in a communal repository of expertise for all of its users. SCALIR's representational scheme also mirrors the hybrid nature of the Anglo-American legal system. While certain legal concepts are precise and rule-like, others -- which legal scholars call "open-textured" -- are subject to interpretation. The meaning of legal text is established through the parallel and distributed precedence-based judicial appeal system. SCALIR represents documents and terms as nodes in a network, capturing the duality of the legal system by using symbolic (semantic network) and connectionist links. The former correspond to a priori knowledge such as the fact that one case overturned another on appeal. The latter correspond to statistical inferences such as the relevance of a term describing a case. SCALIR's text corpus includes all federal cases on copyright law. The hybrid representation also suggests a way to resolve the apparent incompatibility between the two prominent paradigms in artificial intelligence, the "classical" symbol-manipulation approach and the neurally-inspired connectionist approach. Part of the book focuses on a characterization of the two paradigms and an investigation of when and how -- as in the legal research domain -- they can be effectively combined.
Many existing information retrieval (IR) systems are surprisingly ineffective at finding documents relevant to particular topics. Traditional systems are extremely brittle, failing to retrieve relevant documents unless the user's exact search string is found. They support only the most primitive trial-and-error interaction with their users and are also static. Even systems with so-called "relevance feedback" are incapable of learning from experience with users. SCALIR (a Symbolic and Connectionist Approach to Legal Information Retrieval) -- a system for assisting research on copyright law -- has been designed to address these problems. By using a hybrid of symbolic and connectionist artificial intelligence techniques, SCALIR develops a conceptual representation of document relationships without explicit knowledge engineering. SCALIR's direct manipulation interface encourages users to browse through the space of documents. It then uses these browsing patterns to improve its performance by modifying its representation, resulting in a communal repository of expertise for all of its users. SCALIR's representational scheme also mirrors the hybrid nature of the Anglo-American legal system. While certain legal concepts are precise and rule-like, others -- which legal scholars call "open-textured" -- are subject to interpretation. The meaning of legal text is established through the parallel and distributed precedence-based judicial appeal system. SCALIR represents documents and terms as nodes in a network, capturing the duality of the legal system by using symbolic (semantic network) and connectionist links. The former correspond to a priori knowledge such as the fact that one case overturned another on appeal. The latter correspond to statistical inferences such as the relevance of a term describing a case. SCALIR's text corpus includes all federal cases on copyright law. The hybrid representation also suggests a way to resolve the apparent incompatibility between the two prominent paradigms in artificial intelligence, the "classical" symbol-manipulation approach and the neurally-inspired connectionist approach. Part of the book focuses on a characterization of the two paradigms and an investigation of when and how -- as in the legal research domain -- they can be effectively combined.
Book Synopsis A Symbolic and Connectionist Approach To Legal Information Retrieval by : Daniel E. Rose
Download or read book A Symbolic and Connectionist Approach To Legal Information Retrieval written by Daniel E. Rose and published by Psychology Press. This book was released on 2013-06-17 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many existing information retrieval (IR) systems are surprisingly ineffective at finding documents relevant to particular topics. Traditional systems are extremely brittle, failing to retrieve relevant documents unless the user's exact search string is found. They support only the most primitive trial-and-error interaction with their users and are also static. Even systems with so-called "relevance feedback" are incapable of learning from experience with users. SCALIR (a Symbolic and Connectionist Approach to Legal Information Retrieval) -- a system for assisting research on copyright law -- has been designed to address these problems. By using a hybrid of symbolic and connectionist artificial intelligence techniques, SCALIR develops a conceptual representation of document relationships without explicit knowledge engineering. SCALIR's direct manipulation interface encourages users to browse through the space of documents. It then uses these browsing patterns to improve its performance by modifying its representation, resulting in a communal repository of expertise for all of its users. SCALIR's representational scheme also mirrors the hybrid nature of the Anglo-American legal system. While certain legal concepts are precise and rule-like, others -- which legal scholars call "open-textured" -- are subject to interpretation. The meaning of legal text is established through the parallel and distributed precedence-based judicial appeal system. SCALIR represents documents and terms as nodes in a network, capturing the duality of the legal system by using symbolic (semantic network) and connectionist links. The former correspond to a priori knowledge such as the fact that one case overturned another on appeal. The latter correspond to statistical inferences such as the relevance of a term describing a case. SCALIR's text corpus includes all federal cases on copyright law. The hybrid representation also suggests a way to resolve the apparent incompatibility between the two prominent paradigms in artificial intelligence, the "classical" symbol-manipulation approach and the neurally-inspired connectionist approach. Part of the book focuses on a characterization of the two paradigms and an investigation of when and how -- as in the legal research domain -- they can be effectively combined.
Book Synopsis A Symbolic and Connectionist Approach to Legal Information Retrieval by : Daniel Eric Rose
Download or read book A Symbolic and Connectionist Approach to Legal Information Retrieval written by Daniel Eric Rose and published by . This book was released on 1991 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.
Book Synopsis Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing by : Stefan Wermter
Download or read book Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing written by Stefan Wermter and published by Springer Science & Business Media. This book was released on 1996-03-15 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.
Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law. Law students, legal academics and applied information technology specialists are guided thorough all phases of the knowledge discovery from databases process with clear explanations of numerous data mining algorithms including rule induction, neural networks and association rules. Throughout the text, assumptions that make data mining in law quite different to mining other data are made explicit. Issues such as the selection of commonplace cases, the use of discretion as a form of open texture, transformation using argumentation concepts and evaluation and deployment approaches are discussed at length.
Book Synopsis Knowledge Discovery from Legal Databases by : Andrew Stranieri
Download or read book Knowledge Discovery from Legal Databases written by Andrew Stranieri and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law. Law students, legal academics and applied information technology specialists are guided thorough all phases of the knowledge discovery from databases process with clear explanations of numerous data mining algorithms including rule induction, neural networks and association rules. Throughout the text, assumptions that make data mining in law quite different to mining other data are made explicit. Issues such as the selection of commonplace cases, the use of discretion as a form of open texture, transformation using argumentation concepts and evaluation and deployment approaches are discussed at length.
Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR systems.
Book Synopsis Soft Computing in Information Retrieval by : Fabio Crestani
Download or read book Soft Computing in Information Retrieval written by Fabio Crestani and published by Physica. This book was released on 2013-03-19 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR systems.
The gap between information technology and the legal profession is narrowing, in particular due to the Internet and the richness of legal sources that can be found online. This book further bridges the gap by showing people with a legal background what is possible with Information Technology now and in the near future, as well as by showing people with an IT background what opportunities exist in the domain of law.
Book Synopsis Information Technology and Lawyers by : Arno R. Lodder
Download or read book Information Technology and Lawyers written by Arno R. Lodder and published by Springer Science & Business Media. This book was released on 2006-03-06 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: The gap between information technology and the legal profession is narrowing, in particular due to the Internet and the richness of legal sources that can be found online. This book further bridges the gap by showing people with a legal background what is possible with Information Technology now and in the near future, as well as by showing people with an IT background what opportunities exist in the domain of law.
The information age has enabled unprecedented levels of data to be collected and stored. At the same time, society and organizations have become increasingly complex. Consequently, decisions in many facets have become increasingly complex but have the potential to be better informed. Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches includes chapters from diverse fields of enquiry including decision science, political science, argumentation, knowledge management, cognitive psychology and business intelligence. Each chapter illustrates a perspective on group reasoning that ultimately aims to lead to a greater understanding of reasoning communities and inform technological developments.
Book Synopsis Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches by : Yearwood, John
Download or read book Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches written by Yearwood, John and published by IGI Global. This book was released on 2010-10-31 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: The information age has enabled unprecedented levels of data to be collected and stored. At the same time, society and organizations have become increasingly complex. Consequently, decisions in many facets have become increasingly complex but have the potential to be better informed. Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches includes chapters from diverse fields of enquiry including decision science, political science, argumentation, knowledge management, cognitive psychology and business intelligence. Each chapter illustrates a perspective on group reasoning that ultimately aims to lead to a greater understanding of reasoning communities and inform technological developments.
Explains how to build useful tools for searching collections of text and other media.
Book Synopsis Finding Out About by : Richard K. Belew
Download or read book Finding Out About written by Richard K. Belew and published by Cambridge University Press. This book was released on 2000 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains how to build useful tools for searching collections of text and other media.
Book Synopsis Library of Congress Subject Headings by : Library of Congress
Download or read book Library of Congress Subject Headings written by Library of Congress and published by . This book was released on 1994 with total page 1484 pages. Available in PDF, EPUB and Kindle. Book excerpt:
