Search (53 results, page 1 of 3)

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Source

Information storage and retrieval. 3(1967) S.297-314

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Abstract

Information research consists of the comparison of 2 sources of information - that of formal description and content analysis and that based on the needs of the user. Information research filters identical elements from the sources by means of document and research cross-sections. Establishing such cross-sections for scientific documents and research questions is made possible by classification. Through the definition of the terms 'class' and 'classification' it becomes clear that the terms 'hierarchic classification' and 'classification' cannot be used synonymously. The basic types of information research languages are both hierarchic and non-hierarchic arising from the structure of lexicology and the paradigmatic relations of the lexicological units. The names for the lexicological units ('descriptor' and 'subject haedings') are synonymous, but it is necessary to differentiate between the terms 'descriptor language' and 'information research thesaurus'. The principles of precoordination and post-coordination as applied to word formation are unsuitable for the typification of information research languages

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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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Source

Encyclopedia of library and information science. Vol.45, [=Suppl.10]

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Source

Grundlagen der praktischen Information und Dokumentation: eine Einführung. 2. Aufl

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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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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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Source

Grundlagen der praktischen Information und Dokumentation: ein Handbuch zur Einführung in die fachliche Informationsarbeit. 3. Aufl. Hrsg.: M. Buder u.a. Bd.1

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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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Abstract

This paper explores the relationships between natural language lexicons in lexical semantics and thesauri in information retrieval research. These different areas of knowledge have different restrictions on use of vocabulary; thesauri are used only in information search and retrieval contexts, whereas lexicons are mental systems and generally applicable in all domains of life. A set of vocabulary requirements that defines the more concrete characteristics of vocabulary items in the 2 contexts can be derived from this framework: lexicon items have to be learnable, complex, transparent, etc., whereas thesaurus terms must be effective, current and relevant, searchable, etc. The differences in vocabulary properties correlate with 2 other factors, the well-known dimension of Control (deliberate, social activities of building and maintaining vocabularies), and Syntagmatization, which is less known and describes vocabulary items' varying formal preparedness to exit the thesaurus/lexicon, enter into linear syntactic constructions, and, finally, acquire communicative functionality. It is proposed that there is an inverse relationship between Control and Syntagmatization.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.6, S.1480-1490

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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

Footnote

Übers. d. Titels: Integration of information data banks and compatibility of indexing languages

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Abstract

Ich unternehme in diesem Beitrag den Versuch, die Informationswissenschaft - hier gedeutet als 'Information Retrieval'- Disziplin - einer synchronen Querschnittsanalyse zu unterziehen, welche die aktuelle Position dieser Disziplin im Feld anderer zeichen- und wortschatzorientierter Disziplinen (neben der Linguistik die Terminologielehre und die Fachsprachenforschung) näher bestimmen soll. Im Rahmen der Analyse wird von einem Information Retrieval-Kern der Informationswissenschaft ausgegangen, welcher den Informationssuchkontext sowie die Konzepte des Informationsbedarfs und der Relevanz als für diese Disziplin zentrale Komponenten ansieht. Synchron wird das Verhältnis der Informationswissenschaft zu benachbarten Disziplinen durch eine Reihe disziplinspezifischer Zeichenanforderungen erklärt, wodurch ein systemischer Zusammenhang entsteht, der die Informationswissenschaft mit den drei anderen zeichenbezogenen und vokabularorientierten Disziplinen in Beziehung setzt. Das Verhältnis zwischen diesen Disziplinen wird anhand der Dimensionen Kontrolle/Verbindlichkeit sowie Verortung des Vokabulars ("im Kopf" vs. in externen Dokumenten) aufgezeigt, und es wird ein übergeordnetes Prinzip der Syntagmatisierung, welches die beiden Dimensionen vereint, vorgeschlagen.

Source

Information - Wissenschaft und Praxis. 65(2014) H.2, S.99-108

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Footnote

Zitiert in: Evens, M.: Thesaural relations in information retrieval. In: The semantics of relationships: an interdisciplinary perspective. Eds: R. Green u.a. Dordrecht: Kluwer 2002. S.143-160.

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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

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