Search (26 results, page 1 of 2)

0.029919475 = product of:
  0.044879213 = sum of:
    0.023283537 = weight(_text_:to in 1419) [ClassicSimilarity], result of:
      0.023283537 = score(doc=1419,freq=8.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.28121543 = fieldWeight in 1419, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1419)
    0.021595677 = product of:
      0.043191355 = sum of:
        0.043191355 = weight(_text_:22 in 1419) [ClassicSimilarity], result of:
          0.043191355 = score(doc=1419,freq=2.0), product of:
            0.15947726 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045541126 = queryNorm
            0.2708308 = fieldWeight in 1419, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1419)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Because procedures for establishing facets tend toward subjectivity, this pilot project investigates whether the facet structure of a subject literature can be discerned automatically on the basis of its own metadata. Nouns found in the titles of works retrieved from the WorldCat bibliographic database based on Dewey number are mapped against the nodes of the WordNet noun network. Density measures are computed for these nodes to identify nodes best summarizing the title noun data / best corresponding to facets of the subject. Results of the work to date are promising enough to warrant further investigation.

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

0.015827356 = product of:
  0.023741033 = sum of:
    0.008315549 = weight(_text_:to in 2282) [ClassicSimilarity], result of:
      0.008315549 = score(doc=2282,freq=2.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.10043408 = fieldWeight in 2282, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2282)
    0.015425485 = product of:
      0.03085097 = sum of:
        0.03085097 = weight(_text_:22 in 2282) [ClassicSimilarity], result of:
          0.03085097 = score(doc=2282,freq=2.0), product of:
            0.15947726 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045541126 = queryNorm
            0.19345059 = fieldWeight in 2282, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2282)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

The structure of a classification system contributes in a variety of ways to representing semantic relationships between its topics in the context of subject authority control. We explore this claim using the Dewey Decimal Classification (DDC) system as a case study. The DDC links its classes into a notational hierarchy, supplemented by a network of relationships between topics, expressed in class descriptions and in the Relative Index (RI). Topics/subjects are expressed both by the natural language text of the caption and notes (including Manual notes) in a class description and by the controlled vocabulary of the RI's alphabetic index, which shows where topics are treated in the classificatory structure. The expression of relationships between topics depends on paradigmatic and syntagmatic relationships between natural language terms in captions, notes, and RI terms; on the meaning of specific note types; and on references recorded between RI terms. The specific means used in the DDC for capturing hierarchical (including disciplinary), equivalence and associative relationships are surveyed.

Date

8.11.2015 21:27:22

0.008869919 = product of:
  0.026609756 = sum of:
    0.026609756 = weight(_text_:to in 3397) [ClassicSimilarity], result of:
      0.026609756 = score(doc=3397,freq=8.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.32138905 = fieldWeight in 3397, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0625 = fieldNorm(doc=3397)
  0.33333334 = coord(1/3)

Abstract

EPC Exhibit 129-36.1 presented intermediate results of a project to connect Relative Index terms to topics associated with classes and to determine if those Relative Index terms approximated the whole of the corresponding class or were in standing room in the class. The Relative Index project constitutes the first stage of a long(er)-term project to instill a more systematic treatment of relationships within the DDC. The present exhibit sets out a plan of study for that long-term project.

0.00880035 = product of:
  0.026401049 = sum of:
    0.026401049 = weight(_text_:to in 3722) [ClassicSimilarity], result of:
      0.026401049 = score(doc=3722,freq=14.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.3188683 = fieldWeight in 3722, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=3722)
  0.33333334 = coord(1/3)

Abstract

Presents conceptual background. Since topicality is a major factor in relevance, it is crucial to identify the range of relationship types that occur between the topics of user needs and the topics of texts relevant to those needs. Assumes that a single relationship type obtains i.e. that the 2 topics match. Evidence from the analysis of recall failures, citation analysis, and knowledge synthesis suggests otherwise: topical relevance relationships are not limited to topic matching relationships; to the contrary, in certain circumstances they are quite likely not to be matching relationships. Relationships are 1 of the 2 fundamental components of human conceptual systems. Attempts to classify them usually accept a distinction between relationships that occur by virute of the combination of component units (syntagmatic relationships) and relationships that are bulit into the language system (paradigmatic relationships). Given the variety of relationship types previously identified, empirical research is needed to determine the subset that actually account for topical relevance

0.008677262 = product of:
  0.026031785 = sum of:
    0.026031785 = weight(_text_:to in 5159) [ClassicSimilarity], result of:
      0.026031785 = score(doc=5159,freq=10.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.3144084 = fieldWeight in 5159, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5159)
  0.33333334 = coord(1/3)

Abstract

Various shortcomings typically attend thesaural relationships: failure to support extended relevance relationships; lack of effort in identifying a common relational inventory across types of retrieval systems; limitation to binary relationships; inattention to relationships built into the meaning of lexical units. To counteract this failings, a preliminary inventory of relational structures underlying the ca. 1250 most frequently occuring English verbs is presented. The inventory is compact and corresponds to a combination of semantic role-based verb types as identified by Chafe (1970), and image schemata, as identified by Johnson (1987). The nature of hierarchical relationships among relational structures within the inventory is surveyed

0.0081475405 = product of:
  0.02444262 = sum of:
    0.02444262 = weight(_text_:to in 1786) [ClassicSimilarity], result of:
      0.02444262 = score(doc=1786,freq=12.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.29521468 = fieldWeight in 1786, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=1786)
  0.33333334 = coord(1/3)

Abstract

Develops a framework for evaluating the indexing needs of the humanities with reference to 4 set of contrasts: user-oriented vs. document oriented indexing; subject indexing vs. attribute indexing; scientific writing vs. humanistic writing; and topical relevance vs. logical relevance vs. evidential relevance vs. aesthetic relevance. The indexing needs of the humanities range broadly across these contrasts. Established the centrality of relationship to the communication of indexable matter and examines the advantages and disadvantages of means used for their expression in both natural languages and index languages. The use of a relational structure, such as a frame, is shown to represent perhaps the best available option. Illustrates where the use of relational structures in humanities indexing would help meet some of the needs previously identified. The adoption of frame-based indexing in the humanities might substantially improve the retrieval of its literature

Footnote

Contribution to a special issue devoted to papers read at the 1996 Electronic Access to Fiction research seminar at Copenhagen, Denmark

0.0081475405 = product of:
  0.02444262 = sum of:
    0.02444262 = weight(_text_:to in 2201) [ClassicSimilarity], result of:
      0.02444262 = score(doc=2201,freq=12.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.29521468 = fieldWeight in 2201, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=2201)
  0.33333334 = coord(1/3)

Abstract

Claims of bias within the Dewey Decimal Classification (DDC) system in its treatment of indigenous peoples in the U.S. focus on marginalization through ghettoization, historicization, diasporization, and missing topics, such as the status of indigenous peoples as sovereign nations. Investigation into the treatment of indigenous peoples in the U.S. from DDC 16 to DDC 23 reveals that two of the most central concerns, ghettoization and historicization, are not borne out. Diasporization turns out to be a legitimate, but resolvable, concern. The current failure to recognize indigenous peoples as sovereign nations leads to a proposal for a series of expansions in Table 2 for the geographic areas over which indigenous peoples are sovereign; a mismatch between organization by the DDC and by indigenous peoples in the U.S. leads to the supplying of a Manual note table going from names of tribes (a Table 5 concept) to sovereign nations (a Table 2 concept).

0.0077611795 = product of:
  0.023283537 = sum of:
    0.023283537 = weight(_text_:to in 3144) [ClassicSimilarity], result of:
      0.023283537 = score(doc=3144,freq=8.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.28121543 = fieldWeight in 3144, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3144)
  0.33333334 = coord(1/3)

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

0.0074376534 = product of:
  0.02231296 = sum of:
    0.02231296 = weight(_text_:to in 3724) [ClassicSimilarity], result of:
      0.02231296 = score(doc=3724,freq=10.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.26949292 = fieldWeight in 3724, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=3724)
  0.33333334 = coord(1/3)

Abstract

The assumption of topic matching between user needs and texts topically relevant to those needs is often erroneous. Reports an emprical investigantion of the question 'what relationship types actually account for topical relevance'? In order to avoid the bias to topic matching search strategies, user needs are back generated from a randomly selected subset of the subject headings employed in a user oriented topical concordance. The corresponding relevant texts are those indicated in the concordance under the subject heading. Compares the topics of the user needs with the topics of the relevant texts to determine the relationships between them. Topical relevance relationships include a large variety of relationships, only some of which are matching relationships. Others are examples of paradigmatic or syntagmatic relationships. There appear to be no constraints on the kinds of relationships that can function as topical relevance relationships. They are distinguishable from other types of relationships only on functional grounds

0.006721379 = product of:
  0.020164136 = sum of:
    0.020164136 = weight(_text_:to in 110) [ClassicSimilarity], result of:
      0.020164136 = score(doc=110,freq=6.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.24353972 = fieldWeight in 110, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=110)
  0.33333334 = coord(1/3)

Abstract

Preliminary attempts to identify semantic frames and their internal structure automatically have met with a degree of success. In a first stage, clustering is used to detect 4 previously identified semantic frames (COMMERCIAL TRANSACTION, HIT, JUDGING, RISK) from verb definitions in Longman's Dictionary of Contemporary English. In a second stage, nouns used in the definitions of frame-invoking verbs or in whose definitions the frame-invoking verbs occur in certain forms are searched in WordNet to identify frame elements. Suggestions for refinement of the processes are discussed

0.006721379 = product of:
  0.020164136 = sum of:
    0.020164136 = weight(_text_:to in 2236) [ClassicSimilarity], result of:
      0.020164136 = score(doc=2236,freq=6.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.24353972 = fieldWeight in 2236, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2236)
  0.33333334 = coord(1/3)

Content

Relative Index (RI) terms in the Dewey Decimal Classification (DDC) system correspond to concepts that either approximate the whole of the class they index or that are in standing room there. DDC conventions and shallow natural language processing are used to determine automatically whether specific RI terms approximate the whole of or are in standing room in the classes they index. Approximately three-quarters of all RI terms are processed by the techniques described.

0.00627198 = product of:
  0.018815938 = sum of:
    0.018815938 = weight(_text_:to in 6425) [ClassicSimilarity], result of:
      0.018815938 = score(doc=6425,freq=4.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.22725637 = fieldWeight in 6425, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0625 = fieldNorm(doc=6425)
  0.33333334 = coord(1/3)

Abstract

The paper examines the role of attributes within entity-relationship-based conceptual modeling, investigating the interplay between attributes and relationships within (1) data modeling and (2) natural language use. Attribution is found to be an important relationship type. The lack of distinctiveness between attributes and relationships leads to a re-examination of how hierarchy should be treated in both the practice and theory of knowledge organization

0.005761182 = product of:
  0.017283546 = sum of:
    0.017283546 = weight(_text_:to in 7712) [ClassicSimilarity], result of:
      0.017283546 = score(doc=7712,freq=6.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.20874833 = fieldWeight in 7712, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=7712)
  0.33333334 = coord(1/3)

Abstract

Reports results of a study, conducted by Maryland University, College of Library and Information Services, to establish the basic logical design of large scale bibliographic databases using the entity relationship (ER) model, with a view to the eventual conversion of the ER based conceptual schemas into relational databases. A fully normalized relational bibliographic database promises relief from the update, insertion, and deletion anomalies that plague bibliographic databases using MARC formats and USMARC formats internally. Presents the conceptual design of a full scale bibliographic database (inclusing bibliographic, authority, holdings, and classification data), based on entity relationship modelling. This design translates easily into a logical relational design. Discusses the treatment of format integration and the differentiation between the intellectual and bibliographic levels of description and between collective and individual levels of description. Unfortunately, the complexities of bibliographic data result in a tension between the semantic integrity of the relatioal approach and the inefficiencies of normalization and decomposition. Outlines compromise approaches to the dilemma

0.005761182 = product of:
  0.017283546 = sum of:
    0.017283546 = weight(_text_:to in 474) [ClassicSimilarity], result of:
      0.017283546 = score(doc=474,freq=6.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.20874833 = fieldWeight in 474, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=474)
  0.33333334 = coord(1/3)

Abstract

The paper is divided into 3 parts. The 1st develops a framework for evaluating the indexing needs of the humanities with reference to 4 sets of contrasts: user (need)-oriented vs. document-oriented indexing; subject indexing vs. attribute indexing; scientific writing vs. humanistic writing; and topical relevance vs. logical relevance vs. evidential relevance vs. aesthetic relevance. The indexing needs for the humanities range broadly across these contrasts. The 2nd part establishes the centrality of relationships to the communication of indexable matter and examines the advantages and disadvantages of means used for their expression inboth natural languages and indexing languages. The use of relational structure, such as a frame, is shown to represent perhaps the best available option. The 3rd part illustrates where the use of relational structures in humanities indexing would help meet some of the needs previously identified. Although not a panacea, the adoption of frame-based indexing in the humanities might substantially improve the retrieval of its literature

0.005761182 = product of:
  0.017283546 = sum of:
    0.017283546 = weight(_text_:to in 236) [ClassicSimilarity], result of:
      0.017283546 = score(doc=236,freq=6.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.20874833 = fieldWeight in 236, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.046875 = fieldNorm(doc=236)
  0.33333334 = coord(1/3)

Abstract

Semantic types provide a level of abstraction over particulars with shared behavior, such as in the participant structure of semantic frames. The paper presents a preliminary investigation, drawing on data from WordNet and FrameNet, into the relationship between hierarchical level and the semantic types that name frame elements (a.k.a. slots). Patterns discovered include: (1) The level of abstraction of a frame is generally matched by the level of abstraction of its frame elements. (2) The roles played by persons tend to be expressed very specifically. (3) Frame elements that mirror the name of the frame tend to be expressed specifically. (4) Some frame participants tend to be expressed at a constant (general) level of abstraction, regardless of the level of abstraction of the overall frame.

0.0055436995 = product of:
  0.016631098 = sum of:
    0.016631098 = weight(_text_:to in 4823) [ClassicSimilarity], result of:
      0.016631098 = score(doc=4823,freq=8.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.20086816 = fieldWeight in 4823, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4823)
  0.33333334 = coord(1/3)

Abstract

As part of a larger assessment of relationships in the Dewey Decimal Classification (DDC) system, this study investigates the semantic nature of relationships in the DDC notational hierarchy. The semantic relationship between each of a set of randomly selected classes and its parent class in the notational hierarchy is examined against a set of relationship types (specialization, class-instance, several flavours of whole-part).The analysis addresses the prevalence of specific relationship types, their lexical expression, difficulties encountered in assigning relationship types, compatibility of relationships found in the DDC with those found in other knowledge organization systems (KOS), and compatibility of relationships found in the DDC with those in a shared formalism like the Web Ontology Language (OWL). Since notational hierarchy is an organizational mechanism shared across most classification schemes and is often considered to provide an easy solution for ontological transformation of a classification system, the findings of the study are likely to generalize across classification schemes with respect to difficulties that might be encountered in such a transformation process.

Source

Classification and ontology: formal approaches and access to knowledge: proceedings of the International UDC Seminar, 19-20 September 2011, The Hague, The Netherlands. Eds.: A. Slavic u. E. Civallero

0.005487982 = product of:
  0.016463947 = sum of:
    0.016463947 = weight(_text_:to in 3685) [ClassicSimilarity], result of:
      0.016463947 = score(doc=3685,freq=4.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.19884932 = fieldWeight in 3685, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3685)
  0.33333334 = coord(1/3)

Abstract

The significant differences that exist between the print and digital worlds are sometimes felt to diminish the need for bibliographic description in the electronic world. An analysis of these differences, especially with respect to (1) the control of production and distribution of documents and (2) the need for software intermediation, coupled with a discussion of the functions of bibliographic description in the task of document retrieval argue, however, for an increased role for bibliographic description in the electronic world

0.005487982 = product of:
  0.016463947 = sum of:
    0.016463947 = weight(_text_:to in 4475) [ClassicSimilarity], result of:
      0.016463947 = score(doc=4475,freq=4.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.19884932 = fieldWeight in 4475, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4475)
  0.33333334 = coord(1/3)

Abstract

The expression of conceptual syntagmatic relationships in document retrieval systems holds out hope for both increased discrimination generally and increased recall in certain contexts. Such relationships require both a structured inventory of relationships. Examines the means of expressing these. The expression of conceptual syntagmatic relationships must comply with criteria of systematicity, complexity, efficiency and naturalness. Unfortunately, the complex interaction of natural language expression based on lexicalization, word order, function words, and morphosyntactic cases causes failure regarding systematicity. Most methods of expressing conceptual syntagmatic relationships, e.g. term co occurrence techniques, links and role indicators, fail to comply with this and other of the criteria. Only gestalt structures simultaneously representing relationships, participants and roles conform fully to the critical checklist

0.005487982 = product of:
  0.016463947 = sum of:
    0.016463947 = weight(_text_:to in 1150) [ClassicSimilarity], result of:
      0.016463947 = score(doc=1150,freq=4.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.19884932 = fieldWeight in 1150, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1150)
  0.33333334 = coord(1/3)

Abstract

Relevance arises from relationships between user needs and documents/information. In the quest for relevant retrieval, some content-based relationships are best used initially to cast a net that emphasizes recall, while others, both content- and non-content-based, are best used subsequently as filtering devices to achieve better precision. Topical relevance, the primary factor in the initial retrieval operation, extends far beyond topic matching, as often assumed. Empirical studies demonstrate that topical relevance relationships are drawn from a broad but systematic inventory of semantic relationships.

0.005487982 = product of:
  0.016463947 = sum of:
    0.016463947 = weight(_text_:to in 2135) [ClassicSimilarity], result of:
      0.016463947 = score(doc=2135,freq=4.0), product of:
        0.08279609 = queryWeight, product of:
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.045541126 = queryNorm
        0.19884932 = fieldWeight in 2135, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.818051 = idf(docFreq=19512, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2135)
  0.33333334 = coord(1/3)

Abstract

Relationships that interconnect entity classes of import to knowledge organization (knowledge, documents, concepts, beings, information needs, language) include both non-subject bibliographic relationships (document-to-document relationships, responsibility relationships) and conceptual content relationships (subject relationships, relevance relationships). While the MARC format allows the recording of most bibliographic relationships, many of them are not expressed systematically. Conceptual content relationships include, in turn, interconcept and intraconcept relationships. The expression of interconcept relationships is covered by standard thesaural relationships, which typically do not distinguish fully between the underlying lexical relationship types. The full expression of complex intraconcept relationships includes indication of the basic nature of the relationship (including a set of semantic roles), the set of entities that participate in the relationship, and a mapping between participants and semantic roles. Knowledge organization schemes seldom express these relationships fully.