-
Miller, U.; Teitelbaum, R.: Pre-coordination and post-coordination : past and future (2002)
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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.
- Source
- Knowledge organization. 29(2002) no.2, S.87-93
-
Fugmann, R.: Unusual possibilities in indexing and classification (1990)
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- Abstract
- Contemporary research in information science has concentrated on the development of methods for the algorithmic processing of natural language texts. Often, the equivalence of this approach to the intellectual technique of content analysis and indexing is claimed. It is, however, disregarded that contemporary intellectual techniques are far from exploiting their full capabilities. This is largely due to the omission of vocabulary categorisation. It is demonstrated how categorisation can drastically improve the quality of indexing and classification, and, hence, of retrieval
-
Bhattacharyya, G.: ¬A general theory of subject headings (1974)
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- Source
- Library science with a slant to documentation. 11(1974), S.23-29
-
Fugmann, R.: ¬The complementarity of natural and index language in the field of information supply : an overview of their specific capabilities and limitations (2002)
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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.
- Source
- Knowledge organization. 29(2002) nos.3/4, S.217-230
-
¬The semantics of relationships : an interdisciplinary perspective (2002)
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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
- Series
- Information science and knowledge management; vol.3
-
Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991)
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- Date
- 8.10.2000 11:52:22
- Source
- Library science with a slant to documentation. 28(1991) no.4, S.125-130
-
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.
- Source
- Annual review of information science and technology. 40(2006), S.157-228
-
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
-
Boteram, F.: Semantische Relationen in Dokumentationssprachen : vom Thesaurus zum semantischen Netz (2010)
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- Date
- 2. 3.2013 12:29:05
- Source
- Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly
-
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
-
Gilchrist, A.: Structure and function in retrieval (2006)
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- Abstract
- Purpose - This paper forms part of the series "60 years of the best in information research", marking the 60th anniversary of the Journal of Documentation. It aims to review the influence of Brian Vickery's 1971 paper, "Structure and function in retrieval languages". The paper is not an update of Vickery's work, but a comment on a greatly changed environment, in which his analysis still has much validity. Design/methodology/approach - A commentary on selected literature illustrates the continuing relevance of Vickery's ideas. Findings - Generic survey and specific reference are still the main functions of retrieval languages, with minor functional additions such as relevance ranking. New structures are becoming increasingly significant, through developments such as XML. Future development in artificial intelligence hold out new prospects still. Originality/value - The paper shows the continuing relevance of "traditional" ideas of information science from the 1960s and 1970s.
- Source
- Journal of documentation. 62(2006) no.1, S.21-29
-
Mikacic, M.: Statistical system for subject designation (SSSD) for libraries in Croatia (1996)
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- Date
- 31. 7.2006 14:22:21
- Source
- Cataloging and classification quarterly. 22(1996) no.1, S.77-93
-
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.
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- Date
- 6. 1.1999 9:29:10
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Francu, V.: ¬A linguistic approach to information languages (2003)
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- Source
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- Date
- 1. 8.1996 22:01:00
