Search (15 results, page 1 of 1)

0.07529794 = product of:
  0.15059587 = sum of:
    0.08276806 = weight(_text_:data in 772) [ClassicSimilarity], result of:
      0.08276806 = score(doc=772,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.5589768 = fieldWeight in 772, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.125 = fieldNorm(doc=772)
    0.067827806 = product of:
      0.13565561 = sum of:
        0.13565561 = weight(_text_:processing in 772) [ClassicSimilarity], result of:
          0.13565561 = score(doc=772,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.7156181 = fieldWeight in 772, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.125 = fieldNorm(doc=772)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Source

Information processing and management. 23(1987), S.211-224

0.04227614 = product of:
  0.08455228 = sum of:
    0.063356094 = weight(_text_:data in 1167) [ClassicSimilarity], result of:
      0.063356094 = score(doc=1167,freq=12.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.4278775 = fieldWeight in 1167, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1167)
    0.021196188 = product of:
      0.042392377 = sum of:
        0.042392377 = weight(_text_:processing in 1167) [ClassicSimilarity], result of:
          0.042392377 = score(doc=1167,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.22363065 = fieldWeight in 1167, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1167)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

This study systematically compares retrievals on 11 topics across five well-known data bases, with MEDLINE's subject indexing as a focus. Each topic was posed by a researcher in the medical behavioral sciences. Each was searches in MEDLINE, EXCERPTA MEDICA, and PSYCHINFO, which permit descriptor searches, and in SCISEARCH and SOCIAL SCISEARCH, which express topics through cited references. Searches on each topic were made with (1) descriptors, (2) cited references, and (3) natural language (a capabiblity common to all five data bases). The researchers who posed the topics judged the results. In every case, the set of records judged relevant was used to to calculate recall, precision, and novelty ratios. Overall, MEDLINE had the highest recall percentage (37%), followed by SSCI (31%). All searches resulted in high precision ratios; novelty ratios of data bases and searches varied widely. Differences in record format among data bases affected the success of the natural language retrievals. Some 445 documents judged relevant were not retrieved from MEDLINE using its descriptors; they were found in MEDLINE through natural language or in an alternative data base. An analysis was performed to examine possible faults in MEDLINE subject indexing as the reason for their nonretrieval. However, no patterns of indexing failure could be seen in those documents subsequently found in MEDLINE through known-item searches. Documents not found in MEDLINE primarily represent failures of coverage - articles were from nonindexed or selectively indexed journals

Source

Information processing and management. 23(1987), S.539-553

0.031288948 = product of:
  0.062577896 = sum of:
    0.02586502 = weight(_text_:data in 437) [ClassicSimilarity], result of:
      0.02586502 = score(doc=437,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17468026 = fieldWeight in 437, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=437)
    0.036712877 = product of:
      0.073425755 = sum of:
        0.073425755 = weight(_text_:processing in 437) [ClassicSimilarity], result of:
          0.073425755 = score(doc=437,freq=6.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.38733965 = fieldWeight in 437, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.0390625 = fieldNorm(doc=437)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

When bibliometric data are converted to term frequency (tf) and inverse document frequency (idf) values, plotted as pennant diagrams, and interpreted according to Sperber and Wilson's relevance theory (RT), the results evoke major variables of information science (IS). These include topicality, in the sense of intercohesion and intercoherence among texts; cognitive effects of texts in response to people's questions; people's levels of expertise as a precondition for cognitive effects; processing effort as textual or other messages are received; specificity of terms as it affects processing effort; relevance, defined in RT as the effects/effort ratio; and authority of texts and their authors. While such concerns figure automatically in dialogues between people, they become problematic when people create or use or judge literature-based information systems. The difficulty of achieving worthwhile cognitive effects and acceptable processing effort in human-system dialogues explains why relevance is the central concern of IS. Moreover, since relevant communication with both systems and unfamiliar people is uncertain, speakers tend to seek cognitive effects that cost them the least effort. Yet hearers need greater effort, often greater specificity, from speakers if their responses are to be highly relevant in their turn. This theme of mismatch manifests itself in vague reference questions, underdeveloped online searches, uncreative judging in retrieval evaluation trials, and perfunctory indexing. Another effect of least effort is a bias toward topical relevance over other kinds. RT can explain these outcomes as well as more adaptive ones. Pennant diagrams, applied here to a literature search and a Bradford-style journal analysis, can model them. Given RT and the right context, bibliometrics may predict psychometrics.

0.027920479 = product of:
  0.055840958 = sum of:
    0.02586502 = weight(_text_:data in 436) [ClassicSimilarity], result of:
      0.02586502 = score(doc=436,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17468026 = fieldWeight in 436, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=436)
    0.029975938 = product of:
      0.059951875 = sum of:
        0.059951875 = weight(_text_:processing in 436) [ClassicSimilarity], result of:
          0.059951875 = score(doc=436,freq=4.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.3162615 = fieldWeight in 436, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.0390625 = fieldNorm(doc=436)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

In Sperber and Wilson's relevance theory (RT), the ratio Cognitive Effects/Processing Effort defines the relevance of a communication. The tf*idf formula from information retrieval is used to operationalize this ratio for any item co-occurring with a user-supplied seed term in bibliometric distributions. The tf weight of the item predicts its effect on the user in the context of the seed term, and its idf weight predicts the user's processing effort in relating the item to the seed term. The idf measure, also known as statistical specificity, is shown to have unsuspected applications in quantifying interrelated concepts such as topical and nontopical relevance, levels of user expertise, and levels of authority. A new kind of visualization, the pennant diagram, illustrates these claims. The bibliometric distributions visualized are the works cocited with a seed work (Moby Dick), the authors cocited with a seed author (White HD, for maximum interpretability), and the books and articles cocited with a seed article (S.A. Harter's "Psychological Relevance and Information Science," which introduced RT to information scientists in 1992). Pennant diagrams use bibliometric data and information retrieval techniques on the system side to mimic a relevancetheoretic model of cognition on the user side. Relevance theory may thus influence the design of new visual information retrieval interfaces. Generally, when information retrieval and bibliometrics are interpreted in light of RT, the implications are rich: A single sociocognitive theory may serve to integrate research on literature-based systems with research on their users, areas now largely separate.

0.016483411 = product of:
  0.065933645 = sum of:
    0.065933645 = product of:
      0.13186729 = sum of:
        0.13186729 = weight(_text_:22 in 1339) [ClassicSimilarity], result of:
          0.13186729 = score(doc=1339,freq=6.0), product of:
            0.16398162 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046827413 = queryNorm
            0.804159 = fieldWeight in 1339, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=1339)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

22. 2.2003 17:25:39
22. 2.2003 18:16:22

0.012802532 = product of:
  0.051210128 = sum of:
    0.051210128 = weight(_text_:data in 143) [ClassicSimilarity], result of:
      0.051210128 = score(doc=143,freq=4.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.34584928 = fieldWeight in 143, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0546875 = fieldNorm(doc=143)
  0.25 = coord(1/4)

Abstract

This paper shows that, given co-citation data, Kohonen feature mapping produces results quite similar to those of multidimensional scaling, the traditional mode for computer-assisted mapping of intellectual domains. It further presents a Kohonen feature map based on author co-citation data that links author names to information about them on the World Wide Web. The results bear on a goal for present-day information science: the integration of computerized bibliometrics with document retrieval

0.011199882 = product of:
  0.04479953 = sum of:
    0.04479953 = weight(_text_:data in 2119) [ClassicSimilarity], result of:
      0.04479953 = score(doc=2119,freq=6.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.30255508 = fieldWeight in 2119, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2119)
  0.25 = coord(1/4)

Abstract

In their article "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient," Ahlgren, Jarneving, and Rousseau fault traditional author cocitation analysis (ACA) for using Pearson's r as a measure of similarity between authors because it fails two tests of stability of measurement. The instabilities arise when rs are recalculated after a first coherent group of authors has been augmented by a second coherent group with whom the first has little or no cocitation. However, AJ&R neither cluster nor map their data to demonstrate how fluctuations in rs will mislead the analyst, and the problem they pose is remote from both theory and practice in traditional ACA. By entering their own rs into multidimensional scaling and clustering routines, I show that, despite r's fluctuations, clusters based an it are much the same for the combined groups as for the separate groups. The combined groups when mapped appear as polarized clumps of points in two-dimensional space, confirming that differences between the groups have become much more important than differences within the groups-an accurate portrayal of what has happened to the data. Moreover, r produces clusters and maps very like those based an other coefficients that AJ&R mention as possible replacements, such as a cosine similarity measure or a chi square dissimilarity measure. Thus, r performs well enough for the purposes of ACA. Accordingly, I argue that qualitative information revealing why authors are cocited is more important than the cautions proposed in the AJ&R critique. I include notes an topics such as handling the diagonal in author cocitation matrices, lognormalizing data, and testing r for significance.

0.0103460075 = product of:
  0.04138403 = sum of:
    0.04138403 = weight(_text_:data in 2095) [ClassicSimilarity], result of:
      0.04138403 = score(doc=2095,freq=8.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.2794884 = fieldWeight in 2095, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.03125 = fieldNorm(doc=2095)
  0.25 = coord(1/4)

Abstract

Many authors have posited a social component in citation, the consensus being that the citers and citees often have interpersonal as well as intellectual ties. Evidence for this belief has been rather meager, however, in part because social networks researchers have lacked bibliometric data (e.g., pairwise citation counts from online databases), and citation analysts have lacked sociometric data (e.g., pairwise measures of acquaintanceship). In 1997 Nazer extensively measured personal relationships and communication behaviors in what we call "Globenet," an international group of 16 researchers from seven disciplines that was established in 1993 to study human development. Since Globenet's membership is known, it was possible during 2002 to obtain citation records for all members in databases of the Institute for Scientific Information. This permitted examination of how members cited each other (intercited) in journal articles over the past three decades and in a 1999 book to which they all contributed. It was also possible to explore links between the intercitation data and the social and communication data. Using network-analytic techniques, we look at the growth of intercitation over time, the extent to which it follows disciplinary or interdisciplinary lines, whether it covaries with degrees of acquaintanceship, whether it reflects Globenet's organizational structure, whether it is associated with particular in-group communication patterns, and whether it is related to the cocitation of Globenet members. Results show cocitation to be a powerful predictor of intercitation in the journal articles, while being an editor or co-author is an important predictor in the book. Intellectual ties based an shared content did better as predictors than content-neutral social ties like friendship. However, interciters in Globenet communicated more than did noninterciters.

0.009144665 = product of:
  0.03657866 = sum of:
    0.03657866 = weight(_text_:data in 3763) [ClassicSimilarity], result of:
      0.03657866 = score(doc=3763,freq=4.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.24703519 = fieldWeight in 3763, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3763)
  0.25 = coord(1/4)

Abstract

References from publications are at the same time citations to other publications. This entry introduces some of the practical uses of citation data in science and scholarship. At the individual level citations identify and permit the retrieval of specific editions of works, while also suggesting their subject matter, authority, and age. Through citation indexes, retrievals may include not only the earlier items referred to by a given work, but also the later items that cite that given work in turn. Some technical notes on retrieval are included here. Counts of citations received over time, and measures derived from them, reveal the varying impacts of works, authors, journals, organizations, and countries. This has obvious implications for the evaluation of, e.g., library collections, academics, research teams, and science policies. When treated as linkages between pairs of publications, references and citations reveal intellectual ties. Several kinds of links have been defined, such as cocitation, bibliographic coupling, and intercitation. In the aggregate, these links form networks that compactly suggest the intellectual histories of research specialties and disciplines, especially when the networks are visualized through mapping software. Citation analysis is of course not without critics, who have long pointed out imperfections in the data or in analytical techniques. However, the criticisms have generally been met by strong counterarguments from proponents.

0.0074939844 = product of:
  0.029975938 = sum of:
    0.029975938 = product of:
      0.059951875 = sum of:
        0.059951875 = weight(_text_:processing in 5099) [ClassicSimilarity], result of:
          0.059951875 = score(doc=5099,freq=4.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.3162615 = fieldWeight in 5099, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5099)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

This article extends relevance theory (RT) from linguistic pragmatics into information retrieval. Using more than 50 retrieval experiments from the literature as examples, it applies RT to explain the frequency distributions of documents on relevance scales with three or more points. The scale points, which judges in experiments must consider in addition to queries and documents, are communications from researchers. In RT, the relevance of a communication varies directly with its cognitive effects and inversely with the effort of processing it. Researchers define and/or label the scale points to measure the cognitive effects of documents on judges. However, they apparently assume that all scale points as presented are equally easy for judges to process. Yet the notion that points cost variable effort explains fairly well the frequency distributions of judgments across them. By hypothesis, points that cost more effort are chosen by judges less frequently. Effort varies with the vagueness or strictness of scale-point labels and definitions. It is shown that vague scales tend to produce U- or V-shaped distributions, while strict scales tend to produce right-skewed distributions. These results reinforce the paper's more general argument that RT clarifies the concept of relevance in the dialogues of retrieval evaluation.

Source

Information processing and management. 53(2017) no.5, S.1080-1102

0.006466255 = product of:
  0.02586502 = sum of:
    0.02586502 = weight(_text_:data in 1459) [ClassicSimilarity], result of:
      0.02586502 = score(doc=1459,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17468026 = fieldWeight in 1459, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1459)
  0.25 = coord(1/4)

Abstract

In their 1998 article "Visualizing a discipline: An author cocitation analysis of information science, 1972-1995," White and McCain used multidimensional scaling, hierarchical clustering, and factor analysis to display the specialty groupings of 120 highly-cited ("paradigmatic") information scientists. These statistical techniques are traditional in author cocitation analysis (ACA). It is shown here that a newer technique, Pathfinder Networks (PFNETs), has considerable advantages for ACA. In PFNETs, nodes represent authors, and explicit links represent weighted paths between nodes, the weights in this case being cocitation counts. The links can be drawn to exclude all but the single highest counts for author pairs, which reduces a network of authors to only the most salient relationships. When these are mapped, dominant authors can be defined as those with relatively many links to other authors (i.e., high degree centrality). Links between authors and dominant authors define specialties, and links between dominant authors connect specialties into a discipline. Maps are made with one rather than several computer routines and in one rather than many computer passes. Also, PFNETs can, and should, be generated from matrices of raw counts rather than Pearson correlations, which removes a computational step associated with traditional ACA. White and McCain's raw data from 1998 are remapped as a PFNET. It is shown that the specialty groupings correspond closely to those seen in the factor analysis of the 1998 article. Because PFNETs are fast to compute, they are used in AuthorLink, a new Web-based system that creates live interfaces for cocited author retrieval an the fly.

0.006466255 = product of:
  0.02586502 = sum of:
    0.02586502 = weight(_text_:data in 2846) [ClassicSimilarity], result of:
      0.02586502 = score(doc=2846,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17468026 = fieldWeight in 2846, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2846)
  0.25 = coord(1/4)

Abstract

Bibliometric measures for evaluating research units in the book-oriented humanities and social sciences are underdeveloped relative to those available for journal-oriented science and technology. We therefore present a new measure designed for book-oriented fields: the libcitation count. This is a count of the libraries holding a given book, as reported in a national or international union catalog. As librarians decide what to acquire for the audiences they serve, they jointly constitute an instrument for gauging the cultural impact of books. Their decisions are informed by knowledge not only of audiences but also of the book world (e.g., the reputations of authors and the prestige of publishers). From libcitation counts, measures can be derived for comparing research units. Here, we imagine a match-up between the departments of history, philosophy, and political science at the University of New South Wales and the University of Sydney in Australia. We chose the 12 books from each department that had the highest libcitation counts in the Libraries Australia union catalog during 2000 to 2006. We present each book's raw libcitation count, its rank within its Library of Congress (LC) class, and its LC-class normalized libcitation score. The latter is patterned on the item-oriented field normalized citation score used in evaluative bibliometrics. Summary statistics based on these measures allow the departments to be compared for cultural impact. Our work has implications for programs such as Excellence in Research for Australia and the Research Assessment Exercise in the United Kingdom. It also has implications for data mining in OCLC's WorldCat.

0.006466255 = product of:
  0.02586502 = sum of:
    0.02586502 = weight(_text_:data in 4578) [ClassicSimilarity], result of:
      0.02586502 = score(doc=4578,freq=2.0), product of:
        0.14807065 = queryWeight, product of:
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.046827413 = queryNorm
        0.17468026 = fieldWeight in 4578, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.1620505 = idf(docFreq=5088, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4578)
  0.25 = coord(1/4)

Abstract

Just as citations to a book can be counted, so can that book's libcitations-the number of libraries in a consortium that hold it. These holdings counts per title can be obtained from the consortium's union catalog, such as OCLC's WorldCat. Librarians seeking to serve their customers well must be attuned to various kinds of merit in books. The result in WorldCat is a great variation in the libcitations particular books receive. The higher a title's count (or percentile), the more famous it is-either absolutely or within a subject class. Degree of fame also indicates cultural impact, allowing that further documentation of impact may be needed. Using WorldCat data, we illustrate high, medium, and low degrees of fame with 170 titles published during 1990-1995 or 2001-2006 and spanning the 10 main Dewey classes. We use their total libcitation counts or their counts from members of the Association of Research Libraries, or both, as of late 2011. Our analysis of their fame draws on the recognizability of their authors, the extent to which they and their authors are covered by Wikipedia, and whether they have movie or TV versions. Ordinal scales based on Wikipedia coverage and on libcitation counts are very significantly associated.

0.0063588563 = product of:
  0.025435425 = sum of:
    0.025435425 = product of:
      0.05087085 = sum of:
        0.05087085 = weight(_text_:processing in 1080) [ClassicSimilarity], result of:
          0.05087085 = score(doc=1080,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.26835677 = fieldWeight in 1080, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046875 = fieldNorm(doc=1080)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Source

Information processing and management. 39(2003) no.5, S.689-706

0.004239238 = product of:
  0.016956951 = sum of:
    0.016956951 = product of:
      0.033913903 = sum of:
        0.033913903 = weight(_text_:processing in 3872) [ClassicSimilarity], result of:
          0.033913903 = score(doc=3872,freq=2.0), product of:
            0.18956426 = queryWeight, product of:
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.046827413 = queryNorm
            0.17890452 = fieldWeight in 3872, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.048147 = idf(docFreq=2097, maxDocs=44218)
              0.03125 = fieldNorm(doc=3872)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Relevance is the central concept in information science because of its salience in designing and evaluating literature-based answering systems. It is salient when users seek information through human intermediaries, such as reference librarians, but becomes even more so when systems are automated and users must navigate them on their own. Designers of classic precomputer systems of the nineteenth and twentieth centuries appear to have been no less concerned with relevance than the information scientists of today. The concept has, however, proved difficult to define and operationalize. A common belief is that it is a relation between a user's request for information and the documents the system retrieves in response. Documents might be considered retrieval-worthy because they: 1) constitute evidence for or against a claim; 2) answer a question; or 3) simply match the request in topic. In practice, literature-based answering makes use of term-matching technology, and most evaluation of relevance has involved topical match as the primary criterion for acceptability. The standard table for evaluating the relation of retrieved documents to a request has only the values "relevant" and "not relevant," yet many analysts hold that relevance admits of degrees. Moreover, many analysts hold that users decide relevance on more dimensions than topical match. Who then can validly judge relevance? Is it only the person who put the request and who can evaluate a document on multiple dimensions? Or can surrogate judges perform this function on the basis of topicality? Such questions arise in a longstanding debate on whether relevance is objective or subjective. One proposal has been to reframe the debate in terms of relevance theory (imported from linguistic pragmatics), which makes relevance increase with a document's valuable cognitive effects and decrease with the effort needed to process it. This notion allows degree of topical match to contribute to relevance but allows other considerations to contribute as well. Since both cognitive effects and processing effort will differ across users, they can be taken as subjective, but users' decisions can also be objectively evaluated if the logic behind them is made explicit. Relevance seems problematical because the considerations that lead people to accept documents in literature searches, or to use them later in contexts such as citation, are seldom fully revealed. Once they are revealed, relevance may be seen as not only multidimensional and dynamic, but also understandable.