Search (5 results, page 1 of 1)

0.010557194 = product of:
  0.021114388 = sum of:
    0.021114388 = product of:
      0.084457554 = sum of:
        0.084457554 = weight(_text_:authors in 4814) [ClassicSimilarity], result of:
          0.084457554 = score(doc=4814,freq=4.0), product of:
            0.2371355 = queryWeight, product of:
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.05201693 = queryNorm
            0.35615736 = fieldWeight in 4814, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4814)
      0.25 = coord(1/4)
  0.5 = coord(1/2)

Abstract

The authors present a study of the real-life information needs of 59 McGill University undergraduates researching essay topics for either a history or psychology course, interviewed just after they had selected their essay topic. The interview's purpose was to transform the undergraduate's query from general topic terms, based an vague conceptions of their essay topic, to an information need-based query. To chart the transformation, the authors investigate N. J. Belkin, R. N. Oddy, and H. M. Brooks' Anomalous States of Knowledge (ASK) hypothesis (1982a, 1982b), which links the user's ASK to a relevant document set via a common code based an structural facets. In the present study an interoperable structural code based an eight essay styles is created, then notions of structural facets compatible with a highimpact essay structure are presented. The important findings of the study are: (a) the undergraduates' topic statements and terms derived from it do not constitute an effective information need statement because for most of the subjects in the study the topic terms conformed to a low-impact essay style; (b) essay style is an effective interoperable structural code for charting the evolution of the undergraduate's knowledge state from ASK to partial resolution of the ASK in an information need statement.

0.010557194 = product of:
  0.021114388 = sum of:
    0.021114388 = product of:
      0.084457554 = sum of:
        0.084457554 = weight(_text_:authors in 4915) [ClassicSimilarity], result of:
          0.084457554 = score(doc=4915,freq=4.0), product of:
            0.2371355 = queryWeight, product of:
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.05201693 = queryNorm
            0.35615736 = fieldWeight in 4915, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4915)
      0.25 = coord(1/4)
  0.5 = coord(1/2)

Abstract

For millennia humans have sought, organized, and used information as they learned and evolved patterns of human information behaviors to resolve their human problems and survive. However, despite the current focus an living in an "information age," we have a limited evolutionary understanding of human information behavior. In this article the authors examine the current three interdisciplinary approaches to conceptualizing how humans have sought information including (a) the everyday life information seeking-sense-making approach, (b) the information foraging approach, and (c) the problem-solution perspective an information seeking approach. In addition, due to the lack of clarity regarding the rote of information use in information behavior, a fourth information approach is provided based an a theory of information use. The use theory proposed starts from an evolutionary psychology notion that humans are able to adapt to their environment and survive because of our modular cognitive architecture. Finally, the authors begin the process of conceptualizing these diverse approaches, and the various aspects or elements of these approaches, within an integrated model with consideration of information use. An initial integrated model of these different approaches with information use is proposed.

0.010557194 = product of:
  0.021114388 = sum of:
    0.021114388 = product of:
      0.084457554 = sum of:
        0.084457554 = weight(_text_:authors in 197) [ClassicSimilarity], result of:
          0.084457554 = score(doc=197,freq=4.0), product of:
            0.2371355 = queryWeight, product of:
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.05201693 = queryNorm
            0.35615736 = fieldWeight in 197, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.0390625 = fieldNorm(doc=197)
      0.25 = coord(1/4)
  0.5 = coord(1/2)

Abstract

The authors report the findings of a study that analyzes and compares the query logs of PsycINFO for psychology and the two history databases of ABC-Clio: Historical Abstracts and America: History and Life to establish the sociological nature of information need, searching, and seeking in history versus psychology. Two problems are addressed: (a) What level of query log analysis - by individual query terms, by co-occurrence of word pairs, or by multiword terms (MWTs) - best serves as data for categorizing the queries to these two subject-bound databases; and (b) how can the differences in the nature of the queries to history versus psychology databases aid in our understanding of user search behavior and the information needs of their respective users. The authors conclude that MWTs provide the most effective snapshot of user searching behavior for query categorization. The MWTs to ABC-Clio indicate specific instances of historical events, people, and regions, whereas the MWTs to PsycINFO indicate concepts roughly equivalent to descriptors used by PsycINFO's own classification scheme. The average length of queries is 3.16 terms for PsycINFO and 3.42 for ABC-Clio, which breaks from findings for other reference and scholarly search engine studies, bringing query length closer in line to findings for general Web search engines like Excite.

0.00891891 = product of:
  0.01783782 = sum of:
    0.01783782 = product of:
      0.03567564 = sum of:
        0.03567564 = weight(_text_:t in 36) [ClassicSimilarity], result of:
          0.03567564 = score(doc=36,freq=2.0), product of:
            0.20491594 = queryWeight, product of:
              3.9394085 = idf(docFreq=2338, maxDocs=44218)
              0.05201693 = queryNorm
            0.17409891 = fieldWeight in 36, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.9394085 = idf(docFreq=2338, maxDocs=44218)
              0.03125 = fieldNorm(doc=36)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

There have been various approaches to conceptualizing interactive information retrieval (IR), which can be generally divided into system and user approaches (Hearst, 1999; cf. also Spink, 1997). Both system and user approaches define user-system interaction in terms of the system and the user reacting to the actions or behaviors of the other: the system reacts to the user's input; the user to the output of the system (Spink, 1997). In system approach models of the interaction, e.g., Moran (1981), "[T]he user initiates an action or operation and the system responds in some way which in turn leads the user to initiate another action and so on" (Beaulieu, 2000, p. 433). In its purest form, the system approach models the user as a reactive part of the interaction, with the system taking the lead (Bates, 1990). User approaches, on the other hand, in their purest form wish to insert a model of the user in all its socio-cognitive dimensions, to the extent that system designers consider such approaches impractical (Vakkari and Jarvelin, 2005, Chap. 7, this volume). The cognitive approach to IR interaction attempts to overcome this divide (Ruthven, 2005, Chap. 4, this volume; Vakkari and Jarvelin, 2005 Chap. 7, this volume) by representing the cognitive elements of both system designers and the user in the interaction model (Larsen and Ingwersen, 2005 Chap. 3, this volume). There are cognitive approach researchers meeting in a central ground from both the system and user side. On the system side, are computer scientists employing cognitive research to design more effective IR systems from the point of view of the user's task (Nathan, 1990; Fischer, Henninger, and Redmiles, 1991; O'Day and Jeffries, 1993; Russell et al., 1993; Kitajima and Polson, 1996; Terwilliger and Polson, 1997). On the user side are cognitive approach researchers applying methods, concepts and models from psychology to design systems that are more in tune with how users acquire information (e.g., Belkin, 1980; Ford (2005, Chap. 5, this volume); Ingwersen (Larsen and Ingwersen, 2005, Chap. 3, this volume); Saracevic, 1996; Vakkari (Vakkari and Jarvelin, 2005, Chap. 7, this volume)).

0.0070475754 = product of:
  0.014095151 = sum of:
    0.014095151 = product of:
      0.028190302 = sum of:
        0.028190302 = weight(_text_:22 in 642) [ClassicSimilarity], result of:
          0.028190302 = score(doc=642,freq=2.0), product of:
            0.18215442 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05201693 = queryNorm
            0.15476047 = fieldWeight in 642, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=642)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

19. 1.2007 12:55:22