-
Mikacic, M.: Statistical system for subject designation (SSSD) for libraries in Croatia (1996)
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- Abstract
- Describes the developments of the Statistical System for Subject Designation (SSSD): a syntactical system for subject designation for libraries in Croatia, based on the construction of subject headings in agreement with the theory of the sentence nature of subject headings. The discussion is preceded by a brief summary of theories underlying basic principles and fundamental rules of the alphabetical subject catalogue
- Date
- 31. 7.2006 14:22:21
- Source
- Cataloging and classification quarterly. 22(1996) no.1, S.77-93
-
Bodenreider, O.; Bean, C.A.: Relationships among knowledge structures : vocabulary integration within a subject domain (2001)
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- Abstract
- The structure of terminology systems can be seen as one way to organize knowledge. This paper focuses an three types of relationships among terms: synonymy, hierarchical relationships, and explicit mapping relationships. Examples drawn from various medical vocabularies illustrate each type of relationship. The integration of disparate terminological knowledge structures in the Unified Medical Language System is presented and discussed.
- Series
- Information science and knowledge management; vol.2
-
Dextre Clarke, S.G.: Thesaural relationships (2001)
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- Date
- 22. 9.2007 15:45:57
- Series
- Information science and knowledge management; vol.2
-
Zhou, G.D.; Zhang, M.: Extracting relation information from text documents by exploring various types of knowledge (2007)
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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
-
Beghtol, C.: Relationships in classificatory structure and meaning (2001)
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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
-
Evens, M.: Thesaural relations in information retrieval (2002)
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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
-
Relationships in the organization of knowledge (2001)
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- 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
-
Maniez, J.: Fusion de banques de donnees documentaires at compatibilite des languages d'indexation (1997)
0.03
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- Abstract
- Discusses the apparently unattainable goal of compatibility of information languages. While controlled languages can improve retrieval performance within a single system, they make cooperation across different systems more difficult. The Internet and downloading accentuate this adverse outcome and the acceleration of data exchange aggravates the problem of compatibility. Defines this familiar concept and demonstrates that coherence is just as necessary as it was for indexing languages, the proliferation of which has created confusion in grouped data banks. Describes 2 types of potential solutions, similar to those applied to automatic translation of natural languages: - harmonizing the information languages themselves, both difficult and expensive, or, the more flexible solution involving automatic harmonization of indexing formulae based on pre established concordance tables. However, structural incompatibilities between post coordinated languages and classifications may lead any harmonization tools up a blind alley, while the paths of a universal concordance model are rare and narrow
- Date
- 1. 8.1996 22:01:00
-
Khoo, S.G.; Na, J.-C.: Semantic relations in information science (2006)
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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.
-
Mooers, C.N.: ¬The indexing language of an information retrieval system (1985)
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- Abstract
- Calvin Mooers' work toward the resolution of the problem of ambiguity in indexing went unrecognized for years. At the time he introduced the "descriptor" - a term with a very distinct meaning-indexers were, for the most part, taking index terms directly from the document, without either rationalizing them with context or normalizing them with some kind of classification. It is ironic that Mooers' term came to be attached to the popular but unsophisticated indexing methods which he was trying to root out. Simply expressed, what Mooers did was to take the dictionary definitions of terms and redefine them so clearly that they could not be used in any context except that provided by the new definition. He did, at great pains, construct such meanings for over four hundred words; disambiguation and specificity were sought after and found for these words. He proposed that all indexers adopt this method so that when the index supplied a term, it also supplied the exact meaning for that term as used in the indexed document. The same term used differently in another document would be defined differently and possibly renamed to avoid ambiguity. The disambiguation was achieved by using unabridged dictionaries and other sources of defining terminology. In practice, this tends to produce circularity in definition, that is, word A refers to word B which refers to word C which refers to word A. It was necessary, therefore, to break this chain by creating a new, definitive meaning for each word. Eventually, means such as those used by Austin (q.v.) for PRECIS achieved the same purpose, but by much more complex means than just creating a unique definition of each term. Mooers, however, was probably the first to realize how confusing undefined terminology could be. Early automatic indexers dealt with distinct disciplines and, as long as they did not stray beyond disciplinary boundaries, a quick and dirty keyword approach was satisfactory. The trouble came when attempts were made to make a combined index for two or more distinct disciplines. A number of processes have since been developed, mostly involving tagging of some kind or use of strings. Mooers' solution has rarely been considered seriously and probably would be extremely difficult to apply now because of so much interdisciplinarity. But for a specific, weIl defined field, it is still weIl worth considering. Mooers received training in mathematics and physics from the University of Minnesota and the Massachusetts Institute of Technology. He was the founder of Zator Company, which developed and marketed a coded card information retrieval system, and of Rockford Research, Inc., which engages in research in information science. He is the inventor of the TRAC computer language.
- Footnote
- Original in: Information retrieval today: papers presented at an Institute conducted by the Library School and the Center for Continuation Study, University of Minnesota, Sept. 19-22, 1962. Ed. by Wesley Simonton. Minneapolis, Minn.: The Center, 1963. S.21-36.
-
Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991)
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- Date
- 8.10.2000 11:52:22
-
Broughton, V.: Language related problems in the construction of faceted terminologies and their automatic management (2008)
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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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Green, R.: Relationships in the organization of knowledge : an overview (2001)
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- Series
- Information science and knowledge management; vol.2
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Kuhlen, R.: Linguistische Grundlagen (1980)
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- Theme
- Preserved Context Index System (PRECIS)
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Neelameghan, A.: Lateral relationships in multicultural, multilingual databases in the spiritual and religious domains : the OM Information service (2001)
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- Series
- Information science and knowledge management; vol.2
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Milstead, J.L.: Standards for relationships between subject indexing terms (2001)
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- Series
- Information science and knowledge management; vol.2
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Khoo, C.; Chan, S.; Niu, Y.: ¬The many facets of the cause-effect relation (2002)
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- Series
- Information science and knowledge management; vol.3
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Schmitz-Esser, W.: Language of general communication and concept compatibility (1996)
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- Pages
- S.11-22
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¬The semantics of relationships : an interdisciplinary perspective (2002)
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- Series
- Information science and knowledge management; vol.3
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Melton, J.S.: ¬A use for the techniques of structural linguistics in documentation research (1965)
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- Abstract
- Index language (the system of symbols for representing subject content after analysis) is considered as a separate component and a variable in an information retrieval system. It is suggested that for purposes of testing, comparing and evaluating index language, the techniques of structural linguistics may provide a descriptive methodology by which all such languages (hierarchical and faceted classification, analytico-synthetic indexing, traditional subject indexing, indexes and classifications based on automatic text analysis, etc.) could be described in term of a linguistic model, and compared on a common basis
