Search (80 results, page 4 of 4)

0.0018669361 = product of:
  0.016802425 = sum of:
    0.016802425 = weight(_text_:of in 1192) [ClassicSimilarity], result of:
      0.016802425 = score(doc=1192,freq=14.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.2742677 = fieldWeight in 1192, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=1192)
  0.11111111 = coord(1/9)

Abstract

This chapter presents a broad survey of the cause-effect relation, with particular emphasis an how the relation is expressed in text. Philosophers have been grappling with the concept of causation for centuries. Researchers in social psychology have found that the human mind has a very complex mechanism for identifying and attributing the cause for an event. Inferring cause-effect relations between events and statements has also been found to be an important part of reading and text comprehension, especially for narrative text. Though many of the cause-effect relations in text are implied and have to be inferred by the reader, there is also a wide variety of linguistic expressions for explicitly indicating cause and effect. In addition, it has been found that certain words have "causal valence"-they bias the reader to attribute cause in certain ways. Cause-effect relations can also be divided into several different types.

Source

The semantics of relationships: an interdisciplinary perspective. Eds: Green, R., C.A. Bean u. S.H. Myaeng

0.0018669361 = product of:
  0.016802425 = sum of:
    0.016802425 = weight(_text_:of in 1201) [ClassicSimilarity], result of:
      0.016802425 = score(doc=1201,freq=14.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.2742677 = fieldWeight in 1201, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=1201)
  0.11111111 = coord(1/9)

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

Source

The semantics of relationships: an interdisciplinary perspective. Eds: Green, R., C.A. Bean u. S.H. Myaeng

0.0018669361 = product of:
  0.016802425 = sum of:
    0.016802425 = weight(_text_:of in 3835) [ClassicSimilarity], result of:
      0.016802425 = score(doc=3835,freq=14.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.2742677 = fieldWeight in 3835, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=3835)
  0.11111111 = coord(1/9)

Abstract

Word aboutness is defined as the relationship between words and subjects associated with them. An aboutness coefficient is developed to estimate the strength of the aboutness relationship. Words that are randomly distributed across subjects are assumed to lack aboutness and the degree to which their usage deviates from a random pattern indicates the strength of the aboutness. To estimate aboutness, title words and their associated subjects are extracted from the titles of non-fiction English language books in the OCLC WorldCat database. The usage patterns of the title words are analyzed and used to compute aboutness coefficients for each of the common title words. Words with low aboutness coefficients (An and In) are commonly found in stop word lists, whereas words with high aboutness coefficients (Carbonate, Autism) are unambiguous and have a strong subject association. The aboutness coefficient potentially can enhance indexing, advance authority control, and improve retrieval.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.10, S.2471-2483

0.0018595128 = product of:
  0.016735615 = sum of:
    0.016735615 = weight(_text_:of in 4241) [ClassicSimilarity], result of:
      0.016735615 = score(doc=4241,freq=20.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.27317715 = fieldWeight in 4241, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4241)
  0.11111111 = coord(1/9)

Abstract

The purpose of this paper is to formulate an analytical framework for the information concept based on the semiotic theory. Design/methodology/approach The paper is motivated by the apparent controversy that still surrounds the information concept. Information, being a key concept within LIS, suffers from being anchored in various incompatible theories. The paper suggests that information is signs, and it demonstrates how the concept of information can be understood within C.S. Peirce's phenomenologically rooted semiotic. Hence, from there, certain ontological conditions as well epistemological consequences of the information concept can be deduced. Findings The paper argues that an understanding of information, as either objective or subjective/discursive, leads to either objective reductionism and signal processing, that fails to explain how information becomes meaningful at all, or conversely, information is understood only relative to subjective/discursive intentions, agendas, etc. To overcome the limitations of defining information as either objective or subjective/discursive, a semiotic analysis shows that information understood as signs is consistently sensitive to both objective and subjective/discursive features of information. It is consequently argued that information as concept should be defined in relation to ontological conditions having certain epistemological consequences. Originality/value The paper presents an analytical framework, derived from semiotics, that adds to the developments of the philosophical dimensions of information within LIS.

Source

Journal of documentation. 74(2018) no.2, S.372-382

0.0018408239 = product of:
  0.016567415 = sum of:
    0.016567415 = weight(_text_:of in 2381) [ClassicSimilarity], result of:
      0.016567415 = score(doc=2381,freq=10.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.2704316 = fieldWeight in 2381, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2381)
  0.11111111 = coord(1/9)

Abstract

Based upon the existing cognitive theories and available related literature, the hypothesis "Conceptualisation process involves a set of specific cognitive skills" has been evolved. An attempt has been made to identify these cognitive skills that are directly involving in conceptualisation process and the outcome is the identification of 13 cognitve skills that are essential for conceptualisation process. This research is directed towards evolving a new concept classification to facilitate learning and teaching. Here we classify the concepts into six categories based upon their attributes and attribute's relations. A specific "Concept analysis ability" tool is also developed to measure the 'concept analysis ability' of secondary school teachers

0.0018408239 = product of:
  0.016567415 = sum of:
    0.016567415 = weight(_text_:of in 5068) [ClassicSimilarity], result of:
      0.016567415 = score(doc=5068,freq=10.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.2704316 = fieldWeight in 5068, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5068)
  0.11111111 = coord(1/9)

Abstract

This paper deals with different views of lexical semantics. The focus is on the relationship between lexical expressions and conceptual components. First the assumptions about lexicalization and decompositionality of concepts shared by the most semanticists are presented, followed by a discussion of the differences between two-level-semants and one-level-semantics. The final part is concentrated on the interpretation of conceptual components in situations of communication

0.0017640886 = product of:
  0.015876798 = sum of:
    0.015876798 = weight(_text_:of in 2527) [ClassicSimilarity], result of:
      0.015876798 = score(doc=2527,freq=18.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.25915858 = fieldWeight in 2527, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2527)
  0.11111111 = coord(1/9)

Abstract

The evolution of bibliographic classification schemes, from the end of the 19th century to our time, shows a trend of increasing possibilities to combine concepts in a classmark. While the early schemes, like DDC and LCC, were largely enumerative, more and more synthetic devices have appeared with common auxiliaries, facets, and phase relationships. The last editions of UDC and the UDC-derived FATKS project follow this evolution, by introducing more specific phase relationships and more common auxiliaries, like those for general properties and processes. This agrees with the Farradane's principle that each concept should have a place of unique definition, instead of being re-notated in each context where it occurs. This evolution appears to be unfinished, as even in most synthetic schemes many concepts have a different notation according to the disciplinary main classes where they occur. To overcome this limitation, main classes should be defined in terms of phenomena rather than disciplines: the Integrative Level Classification (ILC) research project is currently exploring this possibility. Examples with UDC, FATKS, and ILC notations are discussed.

Content

Beitrag anlässlich: Proceedings of the International Seminar "Information access for the global community", 4-5 June 2007, The Hague. - Vgl.: http://www.udcc.org/seminar07/presentations/gnoli.pdf.

0.0016631988 = product of:
  0.014968789 = sum of:
    0.014968789 = weight(_text_:of in 5071) [ClassicSimilarity], result of:
      0.014968789 = score(doc=5071,freq=16.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24433708 = fieldWeight in 5071, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5071)
  0.11111111 = coord(1/9)

Abstract

The Internet is a giant semiotic system. It is a massive collection of Peirce's three kinds of signs: icons, which show the form of something; indices, which point to something; and symbols, which represent something according to some convention. But current proposals for ontologies and metadata have overlooked some of the most important features of signs. A sign has three aspects: it is (1) an entity that represents (2) another entity to (3) an agent. By looking only at the signs themselves, some metadata proposals have lost sight of the entities they represent and the agents - human, animal, or robot - which interpret them. With its three branches of syntax, semantics, and pragmatics, semiotics provides guidelines for organizing and using signs to represent something to someone for some purpose. Besides representation, semiotics also supports methods for translating patterns of signs intended for one purpose to other patterns intended for different but related purposes. This article shows how the fundamental semiotic primitives are represented in semantically equivalent notations for logic, including controlled natural languages and various computer languages

0.0016631988 = product of:
  0.014968789 = sum of:
    0.014968789 = weight(_text_:of in 2415) [ClassicSimilarity], result of:
      0.014968789 = score(doc=2415,freq=4.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24433708 = fieldWeight in 2415, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.078125 = fieldNorm(doc=2415)
  0.11111111 = coord(1/9)

Source

Discourse and lexical meaning. Proceedings of a Workshop of the DFG Sonderforschungsbereich 340, Stuttgart, 30.11.-1.12.1992. Ed.: P. Bosch u. P. Gerstl

0.0016631988 = product of:
  0.014968789 = sum of:
    0.014968789 = weight(_text_:of in 5457) [ClassicSimilarity], result of:
      0.014968789 = score(doc=5457,freq=16.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24433708 = fieldWeight in 5457, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5457)
  0.11111111 = coord(1/9)

Abstract

Purpose The purpose of this paper is to discuss the literature on concept theory in library and information science (LIS) from an epistemological perspective, ascribing each paper to an epistemological family and discussing their relevance in the context of the knowledge organization (KO) domain. Design/methodology/approach This paper adopts a hermeneutic approach for the analysis of the texts that compose the corpus of study following contingency and categorical analyses. More specifically, the paper works with Bardin's contingency analysis and follows Hjørland's families of epistemologies for the categorization. Findings The analysis corroborates the observations made for the last ten years about the scarcity of studies on concept theory in LIS and KO. However, the study also reveals an epistemological turn on concept theory since 2009 that could be considered a departure from the rationalist views that dominated the field and a continuation of a broader paradigm shift in LIS and KO. All analyzed papers except two follow pragmatist or historicist approaches. Originality/value This paper follows-up and systematizes the contributions to the LIS and KO fields on concept theory mainly during the last decade. The epistemological analysis reveals the dominant views in this paradigm shift and the main authors and trends that are present in the LIS literature on concept theory.

Source

Journal of documentation. 75(2019) no.4, S.876-891

0.0016464829 = product of:
  0.014818345 = sum of:
    0.014818345 = weight(_text_:of in 5673) [ClassicSimilarity], result of:
      0.014818345 = score(doc=5673,freq=2.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24188137 = fieldWeight in 5673, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.109375 = fieldNorm(doc=5673)
  0.11111111 = coord(1/9)

Source

Review of educational research. 61(1991) no.3, S.315-343

0.0016464829 = product of:
  0.014818345 = sum of:
    0.014818345 = weight(_text_:of in 7579) [ClassicSimilarity], result of:
      0.014818345 = score(doc=7579,freq=2.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24188137 = fieldWeight in 7579, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.109375 = fieldNorm(doc=7579)
  0.11111111 = coord(1/9)

0.0016464829 = product of:
  0.014818345 = sum of:
    0.014818345 = weight(_text_:of in 2005) [ClassicSimilarity], result of:
      0.014818345 = score(doc=2005,freq=2.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24188137 = fieldWeight in 2005, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.109375 = fieldNorm(doc=2005)
  0.11111111 = coord(1/9)

0.0016464829 = product of:
  0.014818345 = sum of:
    0.014818345 = weight(_text_:of in 6291) [ClassicSimilarity], result of:
      0.014818345 = score(doc=6291,freq=2.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24188137 = fieldWeight in 6291, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.109375 = fieldNorm(doc=6291)
  0.11111111 = coord(1/9)

0.0016464829 = product of:
  0.014818345 = sum of:
    0.014818345 = weight(_text_:of in 6292) [ClassicSimilarity], result of:
      0.014818345 = score(doc=6292,freq=2.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.24188137 = fieldWeight in 6292, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.109375 = fieldNorm(doc=6292)
  0.11111111 = coord(1/9)

0.0016295954 = product of:
  0.014666359 = sum of:
    0.014666359 = weight(_text_:of in 3254) [ClassicSimilarity], result of:
      0.014666359 = score(doc=3254,freq=6.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.23940048 = fieldWeight in 3254, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0625 = fieldNorm(doc=3254)
  0.11111111 = coord(1/9)

Abstract

The multidimensional language model, as describes in a previous paper (1998, no.2), makes it possible to define a number of concepts, including denotation and signification. Shows that the 'classical semantic triangle', which is commonly used to express denotation and signification, does not contradict the principles of the model. Concludes that the multidimensional language model is a truly universal tool reflecting accurately both semantics and syntax

Footnote

Übers. des Titels: Localisation of denotation and sifnification in a three dimensional language model

0.001577849 = product of:
  0.014200641 = sum of:
    0.014200641 = weight(_text_:of in 1207) [ClassicSimilarity], result of:
      0.014200641 = score(doc=1207,freq=10.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.23179851 = fieldWeight in 1207, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.046875 = fieldNorm(doc=1207)
  0.11111111 = coord(1/9)

Abstract

Specialized domains often come with an extensive terminology, suitable for storing and exchanging information, but not necessarily for knowledge processing. Knowledge structures such as semantic networks, or ontologies, are required to explore the semantics of a domain. The UMLS project at the National Library of Medicine is a research effort to develop knowledge-based resources for the biomedical domain. The Metathesaurus is a large body of knowledge that defines and inter-relates 730,000 biomedical concepts, and the Semantic Network defines the semantic principles that apply to this domain. This chapter presents these two knowledge sources and illustrates through a research study how they can collaborate to further structure the domain. The limits of the approach are discussed.

Source

The semantics of relationships: an interdisciplinary perspective. Eds: Green, R., C.A. Bean u. S.H. Myaeng

0.0015557801 = product of:
  0.0140020205 = sum of:
    0.0140020205 = weight(_text_:of in 3217) [ClassicSimilarity], result of:
      0.0140020205 = score(doc=3217,freq=14.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.22855641 = fieldWeight in 3217, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3217)
  0.11111111 = coord(1/9)

Abstract

In this chapter I propose that frames provide the fundamental representation of knowledge in human cognition. In the first section, I raise problems with the feature list representations often found in theories of knowledge, and I sketch the solutions that frames provide to them. In the second section, I examine the three fundamental concepts of frames: attribute-value sets, structural invariants, and constraints. Because frames also represents the attributes, values, structural invariants, and constraints within a frame, the mechanism that constructs frames builds them recursively. The frame theory I propose borrows heavily from previous frame theories, although its collection of representational components is somewhat unique. Furthermore, frame theorists generally assume that frames are rigid configurations of independent attributes, whereas I propose that frames are dynamic relational structures whose form is flexible and context dependent. In the third section, I illustrate how frames support a wide variety of representational tasks central to conceptual processing in natural and artificial intelligence. Frames can represent exemplars and propositions, prototypes and membership, subordinates and taxonomies. Frames can also represent conceptual combinations, event sequences, rules, and plans. In the fourth section, I show how frames define the extent of conceptual fields and how they provide a powerful productive mechanism for generating specific concepts within a field.

0.001425896 = product of:
  0.0128330635 = sum of:
    0.0128330635 = weight(_text_:of in 58) [ClassicSimilarity], result of:
      0.0128330635 = score(doc=58,freq=6.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.20947541 = fieldWeight in 58, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.0546875 = fieldNorm(doc=58)
  0.11111111 = coord(1/9)

Abstract

This experiment, focused on the users behaviour, aims to study the search topic representation they build and to highlight the role of a graphical thesaurus on their mental models and searching behaviour. The users expertise in the field is considered. The results show how difficult it is to structure a field; they also point out how much a graphical thesaurus could contribute to such a task, but also its restricted role in the query task. They urge us to think over which shape is proper to the conceptual interface and the variety of links that have to be taken into account

Source

Structures and relations in knowledge organization: Proceedings of the 5th International ISKO-Conference, Lille, 25.-29.8.1998. Ed.: W. Mustafa el Hadi et al

0.0011760591 = product of:
  0.010584532 = sum of:
    0.010584532 = weight(_text_:of in 1194) [ClassicSimilarity], result of:
      0.010584532 = score(doc=1194,freq=2.0), product of:
        0.061262865 = queryWeight, product of:
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.03917671 = queryNorm
        0.17277241 = fieldWeight in 1194, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.5637573 = idf(docFreq=25162, maxDocs=44218)
          0.078125 = fieldNorm(doc=1194)
  0.11111111 = coord(1/9)

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.