Search (66 results, page 1 of 4)

0.048416097 = product of:
  0.09683219 = sum of:
    0.09683219 = sum of:
      0.009471525 = weight(_text_:a in 3924) [ClassicSimilarity], result of:
        0.009471525 = score(doc=3924,freq=2.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.17835285 = fieldWeight in 3924, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.109375 = fieldNorm(doc=3924)
      0.087360665 = weight(_text_:22 in 3924) [ClassicSimilarity], result of:
        0.087360665 = score(doc=3924,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.5416616 = fieldWeight in 3924, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.109375 = fieldNorm(doc=3924)
  0.5 = coord(1/2)

Source

Library and information science research. 22(2000) no.4, S.371-382

Type

a

0.020948619 = product of:
  0.041897237 = sum of:
    0.041897237 = sum of:
      0.010696997 = weight(_text_:a in 1177) [ClassicSimilarity], result of:
        0.010696997 = score(doc=1177,freq=20.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.20142901 = fieldWeight in 1177, product of:
            4.472136 = tf(freq=20.0), with freq of:
              20.0 = termFreq=20.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0390625 = fieldNorm(doc=1177)
      0.03120024 = weight(_text_:22 in 1177) [ClassicSimilarity], result of:
        0.03120024 = score(doc=1177,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.19345059 = fieldWeight in 1177, 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=1177)
  0.5 = coord(1/2)

Abstract

Search engine users typically engage in multiquery sessions in their quest to fulfill their information needs. Despite a plethora of research findings suggesting that a significant group of users look for information within a specific geographical scope, existing reformulation studies lack a focused analysis of how users reformulate geographic queries. This study comprehensively investigates the ways in which users reformulate such needs in an attempt to fill this gap in the literature. Reformulated sessions were sampled from a query log of a major search engine to extract 2,400 entries that were manually inspected to filter geo sessions. This filter identified 471 search sessions that included geographical intent, and these sessions were analyzed quantitatively and qualitatively. The results revealed that one in five of the users who reformulated their queries were looking for geographically related information. They reformulated their queries by changing the content of the query rather than the structure. Users were not following a unified sequence of modifications and instead performed a single reformulation action. However, in some cases it was possible to anticipate their next move. A number of tasks in geo modifications were identified, including standard, multi-needs, multi-places, and hybrid approaches. The research concludes that it is important to specialize query reformulation studies to focus on particular query types rather than generically analyzing them, as it is apparent that geographic queries have their special reformulation characteristics.

Date

26. 1.2014 18:48:22

Type

a

0.018982807 = product of:
  0.037965614 = sum of:
    0.037965614 = sum of:
      0.006765375 = weight(_text_:a in 297) [ClassicSimilarity], result of:
        0.006765375 = score(doc=297,freq=8.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.12739488 = fieldWeight in 297, product of:
            2.828427 = tf(freq=8.0), with freq of:
              8.0 = termFreq=8.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0390625 = fieldNorm(doc=297)
      0.03120024 = weight(_text_:22 in 297) [ClassicSimilarity], result of:
        0.03120024 = score(doc=297,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.19345059 = fieldWeight in 297, 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=297)
  0.5 = coord(1/2)

Abstract

In information needs, seeking and use (INSU) research, individuals have most commonly been perceived as users (e.g., Kuhlthau, 1991; Dervin & Nilan, 1986; Dervin, 1989; Belkin, 1980). The concept user originates from the user of libraries and other information services and information systems. Over the years the scope of the concept has become wider and it is nowadays often understood in the sense of seekers of information (e.g., Wilson, 1981; Marchionini, 1995) and users of information (e.g., Streatfield, 1983). Nevertheless, the concept has remained ambiguous by being on the one hand universal and on the other hand extremely specific. The purpose of this paper is to map and evaluate views on people whose information behaviour has been in one way or another the core of our research area. The goal is to shed some light on various relationships between the different aspects of doers in INSU studies. The paper is inspired by Dervin's (1997) analysis of context where she identified among other themes the nature of subject by contrasting a `transcendental individual' with a `decentered subject', and Talja's (1997) presentation about constituting `information' and `user' from the discourse analytic viewpoint as opposed to the cognitive viewpoint. Instead of the metatheoretical approach applied by Dervin and Talja, a more concrete approach is valid in the present analysis where no direct arguments for or against the underlying metatheories are itemised. The focus is on doers in INSU studies leaving other, even closely-related concepts (i.e., information, information seeking, knowledge etc.), outside the scope of the paper.

Date

22. 3.2002 9:55:52

Type

a

0.017992042 = product of:
  0.035984084 = sum of:
    0.035984084 = sum of:
      0.0047838427 = weight(_text_:a in 2680) [ClassicSimilarity], result of:
        0.0047838427 = score(doc=2680,freq=4.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.090081796 = fieldWeight in 2680, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2680)
      0.03120024 = weight(_text_:22 in 2680) [ClassicSimilarity], result of:
        0.03120024 = score(doc=2680,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.19345059 = fieldWeight in 2680, 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=2680)
  0.5 = coord(1/2)

Date

25. 1.2016 18:46:22

Type

a

0.016059995 = product of:
  0.03211999 = sum of:
    0.03211999 = sum of:
      0.0071598003 = weight(_text_:a in 296) [ClassicSimilarity], result of:
        0.0071598003 = score(doc=296,freq=14.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.13482209 = fieldWeight in 296, product of:
            3.7416575 = tf(freq=14.0), with freq of:
              14.0 = termFreq=14.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.03125 = fieldNorm(doc=296)
      0.02496019 = weight(_text_:22 in 296) [ClassicSimilarity], result of:
        0.02496019 = score(doc=296,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.15476047 = fieldWeight in 296, 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=296)
  0.5 = coord(1/2)

Abstract

Previous empirical studies of searcher behaviour have drawn attention to a wide variety of factors that affect performance; for instance, the display of retrieved results can alter search strategies (Allen 1991, 1994), the information need type influences search behaviour, (Elkerton et al 1984, Marchionini 1995); while the task complexity, reflected in the information need can affect user's search behaviour (Large et al 1994). Furthermore, information source selection (Bassilli 1977), and the user's model of the system and domain impact on the search process (Michel 1994); while motivation (Solomon 1993, Jacobsen et al 1992) and the importance of the information need (Wendt 1969) also influence search duration and the effort a user will employ. Rouse and Rouse (1984) in a review of empirical studies, summarise a wide variety of variables that can effect searching behaviour, including payoff, costs of searching, resource available, amount of information sought, characteristics of the data and conflicts between documents. It appears that user behaviour is inconsistent in the search strategies adopted even for the same search need and system (Davidson 1977, Iivonen 1995). Theories of searcher behaviour have been proposed that provide explanations of aspects of end-user behaviour, such as the evolution of the user's information need and the problems of articulating a query, [Bates (1979, 1989), Markey and Atherton 1978], effective search strategies in browsing and goal directed searches [Marchionini 1995, Belkin (1987, 1993)], the linguistic problem of matching search terms with indexing terms or content of target documents through an expert intermediary (Ingwersen 1982) or cognitive aspects of IR (Kulthau 1984, Ingwersen 1996).

Date

22. 3.2002 9:54:13

Type

a

0.0030444188 = product of:
  0.0060888375 = sum of:
    0.0060888375 = product of:
      0.012177675 = sum of:
        0.012177675 = weight(_text_:a in 4440) [ClassicSimilarity], result of:
          0.012177675 = score(doc=4440,freq=18.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.22931081 = fieldWeight in 4440, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4440)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Collating data from a number of log and questionnaire studies conducted largely into the use of a range of consumer health digital information platforms, Centre for Information Behaviour and the Evaluation of Research (Ciber) researchers describe some new thoughts on characterising (and naming) information seeking behaviour in the digital environment, and in so doing, suggest a new typology of digital users. The characteristic behaviour found is one of bouncing in which users seldom penetrate a site to any depth, tend to visit a number of sites for any given information need and seldom return to sites they once visited. They tend to "feed" for information horizontally, and whether they search a site of not depends heavily on "digital visibility", which in turn creates all the conditions for "bouncing". The question whether this type of information seeking represents a form of "dumbing down or up", and what it all means for publishers, librarians and information providers, who might be working on other, possible outdated usage paradigms, is discussed.

Type

a

0.0029294936 = product of:
  0.005858987 = sum of:
    0.005858987 = product of:
      0.011717974 = sum of:
        0.011717974 = weight(_text_:a in 5242) [ClassicSimilarity], result of:
          0.011717974 = score(doc=5242,freq=24.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.22065444 = fieldWeight in 5242, product of:
              4.8989797 = tf(freq=24.0), with freq of:
                24.0 = termFreq=24.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5242)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In "Part 3. Successive Searching.'' where Spink is the primary author, after a review of the work on successive searching, a portion of the Texas generated data is reviewed for insights on how frequently successive searching occurred, the motivation for its occurrence, and any distinctive characteristics of the successive search pattern. Of 18 mediated searches, half requested a second search and a quarter a third search. All but one seeker reported a need to refine and enhance the previous results. Second searches while characterized as refinements included a significantly higher number of items retrieved and more search cycles. Third searches had the most cycles but less retrieved items than the second. Number of terms utilized did not change significantly and overlap was limited to about one in five terms between first and second searches. No overlap occurred between the second and third searches. Problem solving stage shifts did occur with 2 moving to a later stage after the first search, 5 remaining in the same stage and one reverting to a previous stage. Precision did not increase over successive searches, but partial relevant judgments decreased between the second and third search.

Type

a

0.0029000505 = product of:
  0.005800101 = sum of:
    0.005800101 = product of:
      0.011600202 = sum of:
        0.011600202 = weight(_text_:a in 3265) [ClassicSimilarity], result of:
          0.011600202 = score(doc=3265,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.21843673 = fieldWeight in 3265, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3265)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Considers what elicitation or requests for information search intermediaries make of users with information requests during an information retrieval interaction - including prior to and during an information retrieval interaction - and for what purpose. Reports a study of elicitations during 40 mediated information retrieval interactions. Identifies a total of 1.557 search intermediary elicitations within 15 purpose categories. The elicitation purposes of search intermediaries included requests for information on search terms and strategies, database selection, search procedures, system's outputs and relevance of retrieved items, and users' knowledge and previous information seeking. Investigates the transition sequences from 1 type of search intermediary elicitation to another. Compares these findings with results from a study of end user questions

Type

a

0.0029000505 = product of:
  0.005800101 = sum of:
    0.005800101 = product of:
      0.011600202 = sum of:
        0.011600202 = weight(_text_:a in 245) [ClassicSimilarity], result of:
          0.011600202 = score(doc=245,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.21843673 = fieldWeight in 245, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=245)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

A study of the "real world" Web information searching behavior of 206 college students over a 10-month period showed that, contrary to expectations, the users adopted a more passive or browsing approach to Web information searching and became more eclectic in their selection of Web hosts as they gained experience. The study used a longitudinal transaction log analysis of the URLs accessed during 5,431 user days of Web information searching to detect changes in information searching behavior associated with increased experience of using the Web. The findings have implications for the design of future Web information retrieval tools

Type

a

0.0028703054 = product of:
  0.005740611 = sum of:
    0.005740611 = product of:
      0.011481222 = sum of:
        0.011481222 = weight(_text_:a in 5240) [ClassicSimilarity], result of:
          0.011481222 = score(doc=5240,freq=16.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.2161963 = fieldWeight in 5240, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=5240)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In this issue we begin with the first of four parts of a five part series of papers by Spink, Wilson, Ford, Foster, and Ellis. Spink, et alia, in the first section of this report set forth the design of a project to test whether existing models of the information search process are appropriate for an environment of mediated successive searching which they believe characterizes much information seeking behavior. Their goal is to develop an integrated model of the process. Data were collected from 198 individuals, 87 in Texas and 111 in Sheffield in the U.K., with individuals with real information needs engaged in interaction with operational information retrieval systems by use of transaction logs, recordings of interactions with intermediaries, pre, and post search interviews, questionnaire responses, relevance judgments of retrieved text, and responses to a test of cognitive styles. Questionnaires were based upon the Kuhlthau model, the Saracevic model, the Ellis model, and incorporated a visual analog scale to avoid a consistency bias.

Type

a

0.0026849252 = product of:
  0.0053698504 = sum of:
    0.0053698504 = product of:
      0.010739701 = sum of:
        0.010739701 = weight(_text_:a in 3475) [ClassicSimilarity], result of:
          0.010739701 = score(doc=3475,freq=14.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20223314 = fieldWeight in 3475, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3475)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The research reported here was an exploratory study that sought to discover the effects of human individual differences an Web search strategy. These differences consisted of (a) study approaches, (b) cognitive and demographic features, and (c) perceptions of and preferred approaches to Web-based information seeking. Sixtyeight master's students used AItaVista to search for information an three assigned search topics graded in terms of complexity. Five hundred seven search queries were factor analyzed to identify relationships between the individual difference variables and Boolean and best-match search strategies. A number of consistent patterns of relationship were found. As task complexity increased, a number of strategic shifts were also observed an the part of searchers possessing particular combinations of characteristics. A second article (published in this issue of JASIST; Ford, Miller, & Moss, 2005) presents a combined analyses of the data including a series of regression analyses.

Type

a

0.0026849252 = product of:
  0.0053698504 = sum of:
    0.0053698504 = product of:
      0.010739701 = sum of:
        0.010739701 = weight(_text_:a in 3476) [ClassicSimilarity], result of:
          0.010739701 = score(doc=3476,freq=14.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20223314 = fieldWeight in 3476, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3476)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This is the second of two articles published in this issue of JASIST reporting the results of a study investigating relationships between Web search strategies and a range of human individual differences. In this article we provide a combined analysis of the factor analyses previously presented separately in relation to each of three groups of human individual difference (study approaches, cognitive and demographic features, and perceptions of and approaches to Internet-based information seeking). It also introduces two series of regression analyses conducted an data spanning all three individual difference groups. The results are discussed in terms of the extent to which they satisfy the original aim of this exploratory research, namely to identify any relationships between search strategy and individual difference variables for which there is a prima facie case for more focused systematic study. It is argued that a number of such relationships do exist. The results of the project are summarized and suggestions are made for further research.

Type

a

0.0026849252 = product of:
  0.0053698504 = sum of:
    0.0053698504 = product of:
      0.010739701 = sum of:
        0.010739701 = weight(_text_:a in 5232) [ClassicSimilarity], result of:
          0.010739701 = score(doc=5232,freq=14.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20223314 = fieldWeight in 5232, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=5232)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In "Part 2. Uncertainty and Its Correlates,'' where Wilson is the primary author, after a review of uncertainty as a concept in information seeking and decision research, it is hypothesized that if the Kuhlthau problem solving stage model is appropriate the searchers will recognize the stage in which they currently are operating. Secondly to test Wilson's contention that operationalized uncertainty would be useful in characterizing users, it is hypothesized that uncertainty will decrease as the searcher proceeds through problem stages and after the completion of the search. A review of pre and post search interviews reveals that uncertainty can be operationalized, and that academic researchers have no difficulty with a stage model of the information seeking process. Uncertainty is unrelated to sex, age, or discipline, but is related to problem stage and domain knowledge. Both concepts appear robust.

Type

a

0.0026849252 = product of:
  0.0053698504 = sum of:
    0.0053698504 = product of:
      0.010739701 = sum of:
        0.010739701 = weight(_text_:a in 2091) [ClassicSimilarity], result of:
          0.010739701 = score(doc=2091,freq=14.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20223314 = fieldWeight in 2091, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=2091)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching.

Type

a

0.0026742492 = product of:
  0.0053484985 = sum of:
    0.0053484985 = product of:
      0.010696997 = sum of:
        0.010696997 = weight(_text_:a in 301) [ClassicSimilarity], result of:
          0.010696997 = score(doc=301,freq=20.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20142901 = fieldWeight in 301, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=301)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This paper presents the initial stages of the development of a three-dimensional model as a theoretical framework for conceptualizing and exploring interactive information retrieval (IR) with an information seeking context. The model, displayed in Figure 1, includes a Plane of Judgment within a Plane of Interaction within a Plane of Time. The Plane of Judgment includes levels and regions of relevance judgments, and other user judgments during interactive IR, e.g., magnitude or strategy feedback, tactics, search strategies, or search terms. The Plane of Judgment exists within a Plane of Interaction. The Plane of Interaction consists of interactive IR models, including Ingwersen (1992, 1996), Belkin, Cool, Stein and Theil (1995), and Saracevic (1996b, 1997). The Plane of Interaction includes movement or shifts within interactions or search episodes, e.g., tactics, information problem, strategies, terms, feedback, goal states, or uncertainty. IR interactions that occur within a Plane of Interaction exist within a Plane of Time. The Plane of Time includes users' information seeking stages, represented in the model by Kuhlthau's Information Search Process Model (1993) and users' successive searches over time related to the same or evolving information problem (Spink, 1996). The three-dimensional model is a framework for the development of theoretical and empirical research to: 1. Integrate interactive IR research within information-seeking context 2. Explore users' interactive IR episodes within their changing information-seeking contexts 3. Examine relevance judgments within users' information seeking processes 4. Broaden relevance research to include the concurrent exploration of relevance judgment level, region and time

Type

a

0.0026742492 = product of:
  0.0053484985 = sum of:
    0.0053484985 = product of:
      0.010696997 = sum of:
        0.010696997 = weight(_text_:a in 600) [ClassicSimilarity], result of:
          0.010696997 = score(doc=600,freq=20.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20142901 = fieldWeight in 600, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=600)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Recent studies show that humans engage in multitasking behaviors as they seek and search information retrieval (IR) systems for information on more than one topic at the same time. For example, a Web search session by a single user may consist of searching on single topics or multitasking. Findings are presented from four separate studies of the prevalence of multitasking information seeking and searching by Web, IR system, and library users. Incidence of multitasking identified in the four different studies included: (1) users of the Excite Web search engine who completed a survey form, (2) Excite Web search engine users filtered from an Excite transaction log from 20 December 1999, (3) mediated on-line databases searches, and (4) academic library users. Findings include: (1) multitasking information seeking and searching is a common human behavior, (2) users may conduct information seeking and searching on related or unrelated topics, (3) Web or IR multitasking search sessions are longer than single topic sessions, (4) mean number of topics per Web search ranged of 1 to more than 10 topics with a mean of 2.11 topic changes per search session, and (4) many Web search topic changes were from hobbies to shopping and vice versa. A more complex model of human seeking and searching levels that incorporates multitasking information behaviors is presented, and a theoretical framework for human information coordinating behavior (HICB) is proposed. Multitasking information seeking and searching is developing as major research area that draws together IR and information seeking studies toward a focus on IR within the context of human information behavior. Implications for models of information seeking and searching, IR/Web systems design, and further research are discussed.

Type

a

0.0025370158 = product of:
  0.0050740317 = sum of:
    0.0050740317 = product of:
      0.010148063 = sum of:
        0.010148063 = weight(_text_:a in 4400) [ClassicSimilarity], result of:
          0.010148063 = score(doc=4400,freq=18.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.19109234 = fieldWeight in 4400, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4400)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - To explore information behavior from a psychological perspective by relating information seeking to personality traits and study approaches. Design/methodology/approach - The research design was quantitative and consisted of statistical analysis of three questionnaires, i.e. the NEO Five-Factor Inventory measuring personality, the ASSIST test measuring approaches to studying, and a questionnaire regarding information behavior. A total of 305 university students who were in the process of writing a Master's thesis responded to the questionnaires. Findings - Three information-seeking patterns - fast surfing, broad scanning and deep diving - emerged from the statistical analyses. Fast surfing could be related to a surface study approach and emotionality, as well as to low openness to experience and low conscientiousness. Broad scanning was linked to extraversion, openness, and competitiveness, whereas deep diving was a search pattern typical of analytical students with a deep and strategic study approach. Research limitations/implications - The results are based on descriptions of behaviour, not actual observations. Although the statistical results were significant, generalisable conclusions would have required more convincing figures. Further research is recommended in order to explore the three search styles in other populations and contexts. Originality/value - Information-seeking behaviour has not previously been studied in relation to the five-factor model, which is regarded as the most modern personality theory to date. Understanding of the psychological reasons behind different information-seeking styles is important for a holistic view of information behavior. These insights are valuable for researchers interested in user behavior as well as for practitioners like teachers and information professionals.

Type

a

0.0023919214 = product of:
  0.0047838427 = sum of:
    0.0047838427 = product of:
      0.009567685 = sum of:
        0.009567685 = weight(_text_:a in 3539) [ClassicSimilarity], result of:
          0.009567685 = score(doc=3539,freq=4.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18016359 = fieldWeight in 3539, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.078125 = fieldNorm(doc=3539)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Type

a

0.0023919214 = product of:
  0.0047838427 = sum of:
    0.0047838427 = product of:
      0.009567685 = sum of:
        0.009567685 = weight(_text_:a in 1824) [ClassicSimilarity], result of:
          0.009567685 = score(doc=1824,freq=16.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18016359 = fieldWeight in 1824, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1824)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Since the adoption of faceted search in a small number of academic libraries in 2006, faceted search interfaces have gained popularity in academic and public libraries. This article clarifies whether faceted search improves the interactions between searchers and library catalogs and sheds light on ways that facets are used during a library search. To study searchers' behaviors in natural situations, we collected from the servers a data set with more than 1.5 million useful search logs. Logs were parsed, statistically analyzed, and manually studied using visualization tools to gain a general understanding of how facets are used in the search process. A user experiment with 24 subjects was conducted to further understand contextual information, such as the searchers' motivations and perceptions. The results indicate that most searchers were able to understand the concept of facets naturally and easily. The faceted search was not able to shorten the search time but was able to improve the search accuracy. Facets were used more for open-ended tasks and difficult tasks that require more effort to learn, investigate, and explore. Overall, the results weaved a detailed "story" about the ways that people use facets and the ways that facets help people use library catalogs.

Type

a

0.0023678814 = product of:
  0.0047357627 = sum of:
    0.0047357627 = product of:
      0.009471525 = sum of:
        0.009471525 = weight(_text_:a in 3024) [ClassicSimilarity], result of:
          0.009471525 = score(doc=3024,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17835285 = fieldWeight in 3024, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.109375 = fieldNorm(doc=3024)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Type

a