Search (27 results, page 1 of 2)

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Date

22. 9.2007 15:45:57

Series

Information science and knowledge management; vol.2

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Abstract

Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This paper investigates the incorporation of diverse lexical, syntactic and semantic knowledge in feature-based relation extraction using support vector machines. Our study illustrates that the base phrase chunking information is very effective for relation extraction and contributes to most of the performance improvement from syntactic aspect while current commonly used features from full parsing give limited further enhancement. This suggests that most of useful information in full parse trees for relation extraction is shallow and can be captured by chunking. This indicates that a cheap and robust solution in relation extraction can be achieved without decreasing too much in performance. We also demonstrate how semantic information such as WordNet, can be used in feature-based relation extraction to further improve the performance. Evaluation on the ACE benchmark corpora shows that effective incorporation of diverse features enables our system outperform previously best-reported systems. It also shows that our feature-based system significantly outperforms tree kernel-based systems. This suggests that current tree kernels fail to effectively explore structured syntactic information in relation extraction.

Source

Information processing and management. 43(2007) no.4, S.969-982

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Abstract

Thesaural relations have long been used in information retrieval to enrich queries; they have sometimes been used to cluster documents as well. Sometimes the first query to an information retrieval system yields no results at all, or, what can be even more disconcerting, many thousands of hits. One solution is to rephrase the query, improving the choice of query terms by using related terms of different types. A collection of related terms is often called a thesaurus. This chapter describes the lexical-semantic relations that have been used in building thesauri and summarizes some of the effects of using these relational thesauri in information retrieval experiments

Series

Information science and knowledge management; vol.3

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Abstract

Mapping a multidimensional universe of subjects for linear representation, such as in class number, subject heading, and faset structure is problematic. Into this context is recalled the near-seminal and postulational approach suggested by S. R Ranganathan. The non-hierarchical associative relationship or lateral relationship (LR) is distinguished at different levels-among information sources, databases, records of databases, and among concepts (LR-0). Over thirty lateral relationships at the concept level (LR-0) are identified and enumerated with examples from spiritual and religious texts. Special issues relating to LR-0 in multicultural, multilingual databases intended to be used globally by peoples of different cultures and faith are discussed, using as example the multimedia OM Information Service. Vocabulary assistance for users is described.

Series

Information science and knowledge management; vol.2

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Series

Information science and knowledge management; vol.2

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Abstract

Work on relationships takes place in many communities, including, among others, data modeling, knowledge representation, natural language processing, linguistics, and information retrieval. Unfortunately, continued disciplinary splintering and specialization keeps any one person from being familiar with the full expanse of that work. By including contributions form experts in a variety of disciplines and backgrounds, this volume demonstrates both the parallels that inform work on relationships across a number of fields and the singular emphases that have yet to be fully embraced, The volume is organized into 3 parts: (1) Types of relationships (2) Relationships in knowledge representation and reasoning (3) Applications of relationships

Content

Enthält die Beiträge: Pt.1: Types of relationships: CRUDE, D.A.: Hyponymy and its varieties; FELLBAUM, C.: On the semantics of troponymy; PRIBBENOW, S.: Meronymic relationships: from classical mereology to complex part-whole relations; KHOO, C. u.a.: The many facets of cause-effect relation - Pt.2: Relationships in knowledge representation and reasoning: GREEN, R.: Internally-structured conceptual models in cognitive semantics; HOVY, E.: Comparing sets of semantic relations in ontologies; GUARINO, N., C. WELTY: Identity and subsumption; JOUIS; C.: Logic of relationships - Pt.3: Applications of relationships: EVENS, M.: Thesaural relations in information retrieval; KHOO, C., S.H. MYAENG: Identifying semantic relations in text for information retrieval and information extraction; McCRAY, A.T., O. BODENREICHER: A conceptual framework for the biiomedical domain; HETZLER, B.: Visual analysis and exploration of relationships

Series

Information science and knowledge management; vol.3

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Series

Information science and knowledge management; vol.2

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Abstract

In a changing information environment, we need to reassess each element of bibliographic control, including classification theories and systems. Every classification system is a theoretical construct imposed an "reality." The classificatory relationships that are assumed to be valuable have generally received less attention than the topics included in the systems. Relationships are functions of both the syntactic and semantic axes of classification systems, and both explicit and implicit relationships are discussed. Examples are drawn from a number of different systems, both bibliographic and non-bibliographic, and the cultural warrant (i. e., the sociocultural context) of classification systems is examined. The part-whole relationship is discussed as an example of a universally valid concept that is treated as a component of the cultural warrant of a classification system.

Series

Information science and knowledge management; vol.2

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Abstract

With fourteen contributions grouped in two sections, "Theoretical background" and "Systems", this work discusses the most common relationships used in the organization of recorded knowledge to facilitate information retrieval: the relationships between bibliographic entities, intra- and intertextual relationships, relevance relationships, and subject relationships in thesauri and other classificatory structures. The editors' goal is to "spur further interest, debate, research, and development".

Content

Enthält u.a. die Beiträge: GREEN, R.: Relationships in the organization of knowledge: an overview; TILLETT, B.: Bibliographic relationships; CLARKE, S.G.D.: Thesaural relationships; MILSTEAD, J.L.: Standards for relationships between subject indexing terms; HUDON, M.: Relationships in multilingual thesauri; BODENREIDER, O. u. C.A. BEAN: Relationships among knowledge structures: vocabulary integration within a subject domain; BEGHTOL, C.: Relationships in classificatory structure and meaning; BEAN, C.A. u. R. GREEN: Relevance relationships; EL-HOSHY, L.M.: Relationships in Library of Congress Subject Headings; MOLHOLT, P.: The Art and Architecture Thesaurus: controlling relationships through rules and structure; NELSON, S.J. u.a.: Relationships in Medical Subject Headings (MeSH); NEELAMEGHAN, A.: Lateral relationships in multicultural, mulrilingual databases in the spiritual and religous domains: the OM information service; SATIJA, M.P.: Relationships in Ranganathan's Colon classification; MITCHELL, J.S.: Relationships in the Dewey Decimal Classification System

Series

Information science and knowledge management; vol.2

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Information science and knowledge management; vol.2

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Series

Information science and knowledge management; vol.3

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Abstract

This chapter examines the nature of semantic relations and their main applications in information science. The nature and types of semantic relations are discussed from the perspectives of linguistics and psychology. An overview of the semantic relations used in knowledge structures such as thesauri and ontologies is provided, as well as the main techniques used in the automatic extraction of semantic relations from text. The chapter then reviews the use of semantic relations in information extraction, information retrieval, question-answering, and automatic text summarization applications. Concepts and relations are the foundation of knowledge and thought. When we look at the world, we perceive not a mass of colors but objects to which we automatically assign category labels. Our perceptual system automatically segments the world into concepts and categories. Concepts are the building blocks of knowledge; relations act as the cement that links concepts into knowledge structures. We spend much of our lives identifying regular associations and relations between objects, events, and processes so that the world has an understandable structure and predictability. Our lives and work depend on the accuracy and richness of this knowledge structure and its web of relations. Relations are needed for reasoning and inferencing. Chaffin and Herrmann (1988b, p. 290) noted that "relations between ideas have long been viewed as basic to thought, language, comprehension, and memory." Aristotle's Metaphysics (Aristotle, 1961; McKeon, expounded on several types of relations. The majority of the 30 entries in a section of the Metaphysics known today as the Philosophical Lexicon referred to relations and attributes, including cause, part-whole, same and opposite, quality (i.e., attribute) and kind-of, and defined different types of each relation. Hume (1955) pointed out that there is a connection between successive ideas in our minds, even in our dreams, and that the introduction of an idea in our mind automatically recalls an associated idea. He argued that all the objects of human reasoning are divided into relations of ideas and matters of fact and that factual reasoning is founded on the cause-effect relation. His Treatise of Human Nature identified seven kinds of relations: resemblance, identity, relations of time and place, proportion in quantity or number, degrees in quality, contrariety, and causation. Mill (1974, pp. 989-1004) discoursed on several types of relations, claiming that all things are either feelings, substances, or attributes, and that attributes can be a quality (which belongs to one object) or a relation to other objects.
Linguists in the structuralist tradition (e.g., Lyons, 1977; Saussure, 1959) have asserted that concepts cannot be defined on their own but only in relation to other concepts. Semantic relations appear to reflect a logical structure in the fundamental nature of thought (Caplan & Herrmann, 1993). Green, Bean, and Myaeng (2002) noted that semantic relations play a critical role in how we represent knowledge psychologically, linguistically, and computationally, and that many systems of knowledge representation start with a basic distinction between entities and relations. Green (2001, p. 3) said that "relationships are involved as we combine simple entities to form more complex entities, as we compare entities, as we group entities, as one entity performs a process on another entity, and so forth. Indeed, many things that we might initially regard as basic and elemental are revealed upon further examination to involve internal structure, or in other words, internal relationships." Concepts and relations are often expressed in language and text. Language is used not just for communicating concepts and relations, but also for representing, storing, and reasoning with concepts and relations. We shall examine the nature of semantic relations from a linguistic and psychological perspective, with an emphasis on relations expressed in text. The usefulness of semantic relations in information science, especially in ontology construction, information extraction, information retrieval, question-answering, and text summarization is discussed. Research and development in information science have focused on concepts and terms, but the focus will increasingly shift to the identification, processing, and management of relations to achieve greater effectiveness and refinement in information science techniques. Previous chapters in ARIST on natural language processing (Chowdhury, 2003), text mining (Trybula, 1999), information retrieval and the philosophy of language (Blair, 2003), and query expansion (Efthimiadis, 1996) provide a background for this discussion, as semantic relations are an important part of these applications.

Source

Annual review of information science and technology. 40(2006), S.157-228

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Abstract

This article deals with the meaningful processing of information in relation to two systems of Information processing: pre-coordination and post-coordination. The different approaches are discussed, with emphasis an the need for a controlled vocabulary in information retrieval. Assigned indexing, which employs a controlled vocabulary, is described in detail. Types of indexing language can be divided into two broad groups - those using pre-coordinated terms and those depending an post-coordination. They represent two different basic approaches in processing and Information retrieval. The historical development of these two approaches is described, as well as the two tools that apply to these approaches: thesauri and subject headings.

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Content

The paper describes current work on the generation of a thesaurus format from the schedules of the Bliss Bibliographic Classification 2nd edition (BC2). The practical problems that occur in moving from a concept based approach to a terminological approach cluster around issues of vocabulary control that are not fully addressed in a systematic structure. These difficulties can be exacerbated within domains in the humanities because large numbers of culture specific terms may need to be accommodated in any thesaurus. The ways in which these problems can be resolved within the context of a semi-automated approach to the thesaurus generation have consequences for the management of classification data in the source vocabulary. The way in which the vocabulary is marked up for the purpose of machine manipulation is described, and some of the implications for editorial policy are discussed and examples given. The value of the classification notation as a language independent representation and mapping tool should not be sacrificed in such an exercise.

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Abstract

Classification schemes, thesauri, taxonomies, and other controlled vocabularies play important roles in the organization and retrieval of information in many different environments. While the design and construction of controlled vocabularies have been prescribed at the technical level in great detail over the past decades, the methodological level has been somewhat neglected. However, classification research has in recent years focused on developing approaches to the analysis of users, domains, and activities that could produce requirements for the design of controlled vocabularies. Researchers have often argued that the design, construction, and use of controlled vocabularies need to be based on analyses and understandings of the contexts in which these controlled vocabularies function. While one would assume that the growing body of research on human information behavior might help guide the development of controlled vocabularies shed light on these contexts, unfortunately, much of the research in this area is descriptive in nature and of little use for systems design. This paper discusses these trends and outlines a holistic approach that demonstrates how the design of controlled vocabularies can be informed by investigations of people's interactions with information. This approach is based on the Cognitive Work Analysis framework and outlines several dimensions of human-information interactions. Application of this approach will result is a comprehensive understanding of the contexts in which the controlled vocabulary will function and which can be used for the development of for the development of controlled vocabularies.

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Abstract

The aim of this chapter is to demonstrate that semantic issues underlie all research questions within Library and Information Science (LIS, or, as hereafter, IS) and, in particular, the subfield known as Knowledge Organization (KO). Further, it seeks to show that semantics is a field influenced by conflicting views and discusses why it is important to argue for the most fruitful one of these. Moreover, the chapter demonstrates that IS has not yet addressed semantic problems in systematic fashion and examines why the field is very fragmented and without a proper theoretical basis. The focus here is on broad interdisciplinary issues and the long-term perspective. The theoretical problems involving semantics and concepts are very complicated. Therefore, this chapter starts by considering tools developed in KO for information retrieval (IR) as basically semantic tools. In this way, it establishes a specific IS focus on the relation between KO and semantics. It is well known that thesauri consist of a selection of concepts supplemented with information about their semantic relations (such as generic relations or "associative relations"). Some words in thesauri are "preferred terms" (descriptors), whereas others are "lead-in terms." The descriptors represent concepts. The difference between "a word" and "a concept" is that different words may have the same meaning and similar words may have different meanings, whereas one concept expresses one meaning.

Source

Annual review of information science and technology. 41(2007), S.367-405

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Abstract

Natural text phrasing is an indeterminate process and, thus, inherently lacks representational predictability. This holds true in particular in the Gase of general concepts and of their syntactical connectivity. Hence, natural language query phrasing and searching is an unending adventure of trial and error and, in most Gases, has an unsatisfactory outcome with respect to the recall and precision ratlos of the responses. Human indexing is based an knowledgeable document interpretation and aims - among other things - at introducing predictability into the representation of documents. Due to the indeterminacy of natural language text phrasing and image construction, any adequate indexing is also indeterminate in nature and therefore inherently defies any satisfactory algorithmization. But human indexing suffers from a different Set of deficiencies which are absent in the processing of non-interpreted natural language. An optimally effective information System combines both types of language in such a manner that their specific strengths are preserved and their weaknesses are avoided. lf the goal is a large and enduring information system for more than merely known-item searches, the expenditure for an advanced index language and its knowledgeable and careful employment is unavoidable.

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Abstract

A thesaurus is a controlled vocabulary designed to allow for effective information retrieval. It con- sists of different kinds of semantic relationships, with the aim of guiding users to the choice of the most suitable index and search terms for expressing a certain concept. The relational semantics of a thesaurus deal with methods to connect terms with related meanings and arc intended to enhance information recall capabilities. In this paper, focused on hierarchical relations, different aspects of the relational semantics of thesauri, and among them the possibility of developing richer structures, are analyzed. Thesauri are viewed as semantic tools providing, for operational purposes, the representation of the meaning of the terms. The paper stresses how theories of semantics, holding different perspectives about the nature of meaning and how it is represented, affect the design of the relational semantics of thesauri. The need for tools capable of representing the complexity of knowledge and of the semantics of terms as it occurs in the literature of their respective subject fields is advocated. It is underlined how this would contribute to improving the retrieval of information. To achieve this goal, even though in a preliminary manner, we explore the possibility of setting against the framework of thesaurus design the notions of language games and hermeneutic horizon.

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Abstract

Purpose - The purpose of this paper is to summarize the varied structural characteristics which may be present in retrieval languages. Design/methodology/approach - The languages serve varied purposes in information systems, and a number of these are identified. The relations between structure and function are discussed and suggestions made as to the most suitable structures needed for various purposes. Findings - A quantitative approach has been developed: a simple measure is the number of separate terms in a retrieval language, but this has to be related to the scope of its subject field. Some ratio of terms to items in the field seems a more suitable measure of the average specificity of the terms. Other aspects can be quantified - for example, the average number of links in hierarchical chains, or the average number of cross-references in a thesaurus. Originality/value - All the approaches to the analysis of retrieval language reported in this paper are of continuing value. Some practical studies of computer information systems undertaken by Aslib Research Department have suggested a further approach.