Search (65 results, page 1 of 4)

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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.

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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

Purpose The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions. Design/methodology/approach This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions. Findings Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data. Originality/value This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.

Date

22. 1.2021 14:24:32

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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

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

This paper discusses issues concerning the augmentation of thesaurus relationships, in light of new application possibilities for retrieval. We first discuss a case study that explored the retrieval potential of an augmented set of thesaurus relationships by specialising standard relationships into richer subtypes, in particular hierarchical geographical containment and the associative relationship. We then locate this work in a broader context by reviewing various attempts to build taxonomies of thesaurus relationships, and conclude by discussing the feasibility of hierarchically augmenting the core set of thesaurus relationships, particularly the associative relationship. We discuss the possibility of enriching the specification and semantics of Related Term (RT relationships), while maintaining compatibility with traditional thesauri via a limited hierarchical extension of the associative (and hierarchical) relationships. This would be facilitated by distinguishing the type of term from the (sub)type of relationship and explicitly specifying semantic categories for terms following a faceted approach. We first illustrate how hierarchical spatial relationships can be used to provide more flexible retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted the potential of RTs in thesaurus search aids but also the problem of uncontrolled expansion of query term sets. Results presented in this paper suggest the potential for taking account of the hierarchical context of an RT link and specialisations of the RT relationship

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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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.

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Abstract

Effective use of syntagmatic relationships in index languages has suffered from inaccurate or incomplete characterization in both linguistics and information science. A number of 'myths' about syntagmatic relationships are debunked: the exclusivity of paradigmatic and syntagmatic relationships, linearity as a defining characteristic of syntagmatic relationships, the restriction of syntagmatic relationships to surface linguistic units, the limitation of syntagmatic relationship benefits in document retrieval to precision, and the general irrelevance of syntagmatic relationships for document retrieval. None of the mechanisms currently used with index languages is powerful enough to achieve the levels of precision and recall that the expression of conceptual syntagmatic relationships is in theory capable of. New designs for expressing these relationships in index languages will need to take into account such characteristics as their semantic nature, systematicity, generalizability and constituent nature

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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

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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

To illustrate the theoretical analysis presented by J. Maniez published in Documentaliste 34(1997) nos.4/5 presents some concrete examples drawn for experience of the difficulties increasingly faced in trying to make different indexing languages compatible. Various types of problems may be considered: comparing semantic terms and relationships that compose indexing languages, setting standards for writing and vocabulary, and opposing pre and post coordinated descriptors. Proposes several solutions and discusses the need for further applied research in this area

Date

1. 8.1996 22:01:00

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Abstract

A thesaurus in the controlled vocabulary environment is a tool designed to support effective infonnation retrieval (IR) by guiding indexers and searchers consistently to choose the same terms for expressing a given concept or combination of concepts. Terms in the thesaurus are linked by relationships of three well-known types: equivalence, hierarchical, and associative. The functions and properties of these three basic types and some subcategories are described, as well as some additional relationship types conunonly found in thesauri. Progressive automation of IR processes and the capability for simultaneous searching of vast networked resources are creating some pressures for change in the categorization and consistency of relationships.

Date

22. 9.2007 15:45:57

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Abstract

Moderne Verfahren des Information Retrieval verlangen nach aussagekräftigen und detailliert relationierten Dokumentationssprachen. Der selektive Transfer einzelner Modellierungsstrategien aus dem Bereich semantischer Technologien für die Gestaltung und Relationierung bestehender Dokumentationssprachen wird diskutiert. In Form einer Taxonomie wird ein hierarchisch strukturiertes Relationeninventar definiert, welches sowohl hinreichend allgemeine als auch zahlreiche spezifische Relationstypen enthält, die eine detaillierte und damit aussagekräftige Relationierung des Vokabulars ermöglichen. Das bringt einen Zugewinn an Übersichtlichkeit und Funktionalität. Im Gegensatz zu anderen Ansätzen und Überlegungen zur Schaffung von Relationeninventaren entwickelt der vorgestellte Vorschlag das Relationeninventar aus der Begriffsmenge eines bestehenden Gegenstandsbereichs heraus.

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

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Abstract

Although less well studied than noun polysemy, verb polysemy affects both natural language and controlled vocabulary searching. This paper reports the preliminary conclusions of an empirical investigation of the semantic relationships between ca. 600 verb sense pairs in English, illustrating six classes of semantic relationships that account for a significant proportion of verbal polysemy.

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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

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Source

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

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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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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.

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Abstract

The terminological consistency of indexers working with a thesaurus as indexing aid remains low. This suggests that indexers cannot perceive easily or very clearly the meaning of each descriptor available as index term. This paper presents the background nd some of the findings of a small scale experiment designed to study the effect on interindexer terminological consistency of modifying the nature of the semantic information given with descriptors in a thesaurus. The study also provided some insights into the respective usefulness of standardized definitions and of traditional networks of hierarchical and associative relationships as means of providing essential meaning information in the thesaurus used as indexing aid

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Abstract

The paper presents the rationale, significance, method and procedure of building a taxonomy of semantic relations in the oil spill domain for supporting knowledge discovery through inference. Difficult problems during the development of the taxonomy are discussed and partial solutions are proposed. A preliminary functional evaluation of the taxonomy for supporting knowledge discovery was performed. Durability an expansibility of the taxonomy were evaluated by using the taxonomy to classifying the terms in a biomedical relation ontology. The taxonomy was found to have full expansibility and high degree of durability. The study proposes more research problems than solutions.

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