Search (270 results, page 3 of 14)

  • × theme_ss:"Suchtaktik"
  1. Kellar, M.; Watters, C.; Shepherd, M.: ¬A field study characterizing Web-based information seeking tasks (2007) 0.01
    0.009083285 = product of:
      0.063582994 = sum of:
        0.04931406 = weight(_text_:web in 335) [ClassicSimilarity], result of:
          0.04931406 = score(doc=335,freq=16.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.5099235 = fieldWeight in 335, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=335)
        0.014268933 = weight(_text_:information in 335) [ClassicSimilarity], result of:
          0.014268933 = score(doc=335,freq=16.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.27429342 = fieldWeight in 335, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=335)
      0.14285715 = coord(2/14)
    
    Abstract
    Previous studies have examined various aspects of user behavior on the Web, including general information-seeking patterns, search engine use, and revisitation habits. Little research has been conducted to study how users navigate and interact with their Web browser across different information-seeking tasks. We have conducted a field study of 21 participants, in which we logged detailed Web usage and asked participants to provide task categorizations of their Web usage based on the following categories: Fact Finding, Information Gathering, Browsing, and Transactions. We used implicit measures logged during each task session to provide usage measures such as dwell time, number of pages viewed, and the use of specific browser navigation mechanisms. We also report on differences in how participants interacted with their Web browser across the range of information-seeking tasks. Within each type of task, we found several distinguishing characteristics. In particular, Information Gathering tasks were the most complex; participants spent more time completing this task, viewed more pages, and used the Web browser functions most heavily during this task. The results of this analysis have been used to provide implications for future support of information seeking on the Web as well as direction for future research in this area.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.7, S.999-1018
  2. Spink, A.; Goodrum, A.; Robins, D.: Elicitation behavior during mediated information retrieval (1998) 0.01
    0.009018487 = product of:
      0.06312941 = sum of:
        0.021188283 = weight(_text_:information in 3265) [ClassicSimilarity], result of:
          0.021188283 = score(doc=3265,freq=18.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.40730494 = fieldWeight in 3265, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3265)
        0.04194113 = weight(_text_:retrieval in 3265) [ClassicSimilarity], result of:
          0.04194113 = score(doc=3265,freq=8.0), product of:
            0.08963835 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.029633347 = queryNorm
            0.46789268 = fieldWeight in 3265, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3265)
      0.14285715 = coord(2/14)
    
    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
    Source
    Information processing and management. 34(1998) nos.2/3, S.257-273
  3. Saastamoinen, M.; Järvelin, K.: Search task features in work tasks of varying types and complexity (2017) 0.01
    0.009004591 = product of:
      0.042021424 = sum of:
        0.016016837 = weight(_text_:information in 3589) [ClassicSimilarity], result of:
          0.016016837 = score(doc=3589,freq=14.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.3078936 = fieldWeight in 3589, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=3589)
        0.01797477 = weight(_text_:retrieval in 3589) [ClassicSimilarity], result of:
          0.01797477 = score(doc=3589,freq=2.0), product of:
            0.08963835 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.029633347 = queryNorm
            0.20052543 = fieldWeight in 3589, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=3589)
        0.008029819 = product of:
          0.024089456 = sum of:
            0.024089456 = weight(_text_:22 in 3589) [ClassicSimilarity], result of:
              0.024089456 = score(doc=3589,freq=2.0), product of:
                0.103770934 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.029633347 = queryNorm
                0.23214069 = fieldWeight in 3589, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3589)
          0.33333334 = coord(1/3)
      0.21428572 = coord(3/14)
    
    Abstract
    Information searching in practice seldom is an end in itself. In work, work task (WT) performance forms the context, which information searching should serve. Therefore, information retrieval (IR) systems development/evaluation should take the WT context into account. The present paper analyzes how WT features: task complexity and task types, affect information searching in authentic work: the types of information needs, search processes, and search media. We collected data on 22 information professionals in authentic work situations in three organization types: city administration, universities, and companies. The data comprise 286 WTs and 420 search tasks (STs). The data include transaction logs, video recordings, daily questionnaires, interviews. and observation. The data were analyzed quantitatively. Even if the participants used a range of search media, most STs were simple throughout the data, and up to 42% of WTs did not include searching. WT's effects on STs are not straightforward: different WT types react differently to WT complexity. Due to the simplicity of authentic searching, the WT/ST types in interactive IR experiments should be reconsidered.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1111-1123
  4. White, M.D.; Iivonen, M.: Questions as a factor in Web search strategy (2001) 0.01
    0.008991993 = product of:
      0.06294395 = sum of:
        0.048818428 = weight(_text_:web in 333) [ClassicSimilarity], result of:
          0.048818428 = score(doc=333,freq=2.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.50479853 = fieldWeight in 333, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.109375 = fieldNorm(doc=333)
        0.014125523 = weight(_text_:information in 333) [ClassicSimilarity], result of:
          0.014125523 = score(doc=333,freq=2.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.27153665 = fieldWeight in 333, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.109375 = fieldNorm(doc=333)
      0.14285715 = coord(2/14)
    
    Source
    Information processing and management. 37(2001) no.5, S.721-740
  5. Kinley, K.; Tjondronegoro, D.; Partridge, H.; Edwards, S.: Modeling users' web search behavior and their cognitive styles (2014) 0.01
    0.008810189 = product of:
      0.061671317 = sum of:
        0.04931406 = weight(_text_:web in 1281) [ClassicSimilarity], result of:
          0.04931406 = score(doc=1281,freq=16.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.5099235 = fieldWeight in 1281, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1281)
        0.012357258 = weight(_text_:information in 1281) [ClassicSimilarity], result of:
          0.012357258 = score(doc=1281,freq=12.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.23754507 = fieldWeight in 1281, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1281)
      0.14285715 = coord(2/14)
    
    Abstract
    Previous studies have shown that users' cognitive styles play an important role during web searching. However, only a limited number of studies have showed the relationship between cognitive styles and web search behavior. Most importantly, it is not clear which components of web search behavior are influenced by cognitive styles. This article examines the relationships between users' cognitive styles and their web searching and develops a model that portrays the relationship. The study uses qualitative and quantitative analyses based on data gathered from 50 participants. A questionnaire was utilized to collect participants' demographic information, and Riding's (1991) Cognitive Styles Analysis (CSA) test to assess their cognitive styles. Results show that users' cognitive styles influenced their information-searching strategies, query reformulation behavior, web navigational styles, and information-processing approaches. The user model developed in this study depicts the fundamental relationships between users' web search behavior and their cognitive styles. Modeling web search behavior with a greater understanding of users' cognitive styles can help information science researchers and information systems designers to bridge the semantic gap between the user and the systems. Implications of the research for theory and practice, and future work, are discussed.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1107-1123
  6. Mohan, K.C.: Boolean and nearest neighbour text searching in a multi-strategy retrieval system (1996) 0.01
    0.008478267 = product of:
      0.059347864 = sum of:
        0.011415146 = weight(_text_:information in 7255) [ClassicSimilarity], result of:
          0.011415146 = score(doc=7255,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.21943474 = fieldWeight in 7255, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0625 = fieldNorm(doc=7255)
        0.047932718 = weight(_text_:retrieval in 7255) [ClassicSimilarity], result of:
          0.047932718 = score(doc=7255,freq=8.0), product of:
            0.08963835 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.029633347 = queryNorm
            0.5347345 = fieldWeight in 7255, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0625 = fieldNorm(doc=7255)
      0.14285715 = coord(2/14)
    
    Abstract
    Information retrieval systems based on the Boolean model have been popular for some time. A major challenge to this model has come from the development of approaches based on the vector processing model. Both search strategies are explained and evaluated. Describes an experimental study in an opertational environment to compare the retrieval effectiveness of Boolean and nearest neighbour searching in a multi-strategy retrieval system based on query characteristic variables. Considers the significance of the results of the study
    Source
    Library science with a slant to documentation and information studies. 33(1996) no.1, S.29-38
  7. Kim, K.-S.; Allen, B.: Cognitive and task influences on Web searching behavior (2002) 0.01
    0.008400954 = product of:
      0.05880668 = sum of:
        0.048818428 = weight(_text_:web in 199) [ClassicSimilarity], result of:
          0.048818428 = score(doc=199,freq=8.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.50479853 = fieldWeight in 199, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=199)
        0.009988253 = weight(_text_:information in 199) [ClassicSimilarity], result of:
          0.009988253 = score(doc=199,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.1920054 = fieldWeight in 199, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=199)
      0.14285715 = coord(2/14)
    
    Abstract
    Users' individual differences and tasks are important factors that influence the use of information systems. Two independent investigations were conducted to study the impact of differences in users' cognition and search tasks on Web search activities and outcomes. Strong task effects were found on search activities and outcomes, whereas interactions between cognitive and task variables were found on search activities only. These results imply that the flexibility of the Web and Web search engines allows different users to complete different search tasks successfully. However, the search techniques used and the efficiency of the searches appear to depend on how well the individual searcher fits with the specific task
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.2, S.109-119
  8. Kim, K.-S.: Effects of emotion control and task on Web searching behavior (2008) 0.01
    0.008400954 = product of:
      0.05880668 = sum of:
        0.048818428 = weight(_text_:web in 891) [ClassicSimilarity], result of:
          0.048818428 = score(doc=891,freq=8.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.50479853 = fieldWeight in 891, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=891)
        0.009988253 = weight(_text_:information in 891) [ClassicSimilarity], result of:
          0.009988253 = score(doc=891,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.1920054 = fieldWeight in 891, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=891)
      0.14285715 = coord(2/14)
    
    Abstract
    The study investigated how users' emotion control and search tasks interact and influence the Web search behavior and performance among experienced Web users. Sixty-seven undergraduate students with substantial Web experience participated in the study. Effects of emotion control and tasks were found significant on the search behavior but not on the search performance. The interaction effect between emotion control and tasks on the search behavior was also significant: effects of users' emotion control on the search behavior varied depending on search tasks. Profile analyses of search behaviors identified and contrasted the most commonly occurring profiles of search activities in different search tasks. Suggestions were made to improve information literacy programs, and implications for future research were discussed.
    Source
    Information processing and management. 44(2008) no.1, S.373-385
  9. Bhavnani, S.K.: Why is it difficult to find comprehensive information? : implications of information scatter for search and design (2005) 0.01
    0.0083800545 = product of:
      0.05866038 = sum of:
        0.042707227 = weight(_text_:web in 3684) [ClassicSimilarity], result of:
          0.042707227 = score(doc=3684,freq=12.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.4416067 = fieldWeight in 3684, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3684)
        0.015953152 = weight(_text_:information in 3684) [ClassicSimilarity], result of:
          0.015953152 = score(doc=3684,freq=20.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.30666938 = fieldWeight in 3684, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3684)
      0.14285715 = coord(2/14)
    
    Abstract
    The rapid development of Web sites providing extensive coverage of a topic, coupled with the development of powerful search engines (designed to help users find such Web sites), suggests that users can easily find comprehensive information about a topic. In domains such as consumer healthcare, finding comprehensive information about a topic is critical as it can improve a patient's judgment in making healthcare decisions, and can encourage higher compliance with treatment. However, recent studies show that despite using powerful search engines, many healthcare information seekers have difficulty finding comprehensive information even for narrow healthcare topics because the relevant information is scattered across many Web sites. To date, no studies have analyzed how facts related to a search topic are distributed across relevant Web pages and Web sites. In this study, the distribution of facts related to five common healthcare topics across high-quality sites is analyzed, and the reasons underlying those distributions are explored. The analysis revealed the existence of few pages that had many facts, many pages that had few facts, and no single page or site that provided all the facts. While such a distribution conforms to other information-related phenomena, a deeper analysis revealed that the distributions were caused by a trade-off between depth and breadth, leading to the existence of general, specialized, and sparse pages. Furthermore, the results helped to make explicit the knowledge needed by searchers to find comprehensive healthcare information, and suggested the motivation to explore distribution-conscious approaches for the development of future search systems, search interfaces, Web page designs, and training.
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.9, S.989-1003
  10. Thatcher, A.: Web search strategies : the influence of Web experience and task type (2008) 0.01
    0.008064075 = product of:
      0.056448527 = sum of:
        0.04931406 = weight(_text_:web in 2095) [ClassicSimilarity], result of:
          0.04931406 = score(doc=2095,freq=16.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.5099235 = fieldWeight in 2095, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2095)
        0.0071344664 = weight(_text_:information in 2095) [ClassicSimilarity], result of:
          0.0071344664 = score(doc=2095,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.13714671 = fieldWeight in 2095, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2095)
      0.14285715 = coord(2/14)
    
    Abstract
    Despite a number of studies looking at Web experience and Web searching tactics and behaviours, the specific relationships between experience and cognitive search strategies have not been widely researched. This study investigates how the cognitive search strategies of 80 participants might vary with Web experience as they engaged in two researcher-defined tasks and two participant-defined information seeking tasks. Each of the two researcher-defined tasks and participant-defined tasks included a directed search task and a general-purpose browsing task. While there were almost no significant performance differences between experience levels on any of the four tasks, there were significant differences in the use of cognitive search strategies. Participants with higher levels of Web experience were more likely to use "Parallel player", "Parallel hub-and-spoke", "Known address search domain" and "Known address" strategies, whereas participants with lower levels of Web experience were more likely to use "Virtual tourist", "Link-dependent", "To-the-point", "Sequential player", "Search engine narrowing", and "Broad first" strategies. The patterns of use and differences between researcher-defined and participant-defined tasks and between directed search tasks and general-purpose browsing tasks are also discussed, although the distribution of search strategies by Web experience were not statistically significant for each individual task.
    Source
    Information processing and management. 44(2008) no.3, S.1308-1329
  11. Hsieh-Yee, I.: Search tactics of Web users in searching for texts, graphics, known items and subjects : a search simulation study (1998) 0.01
    0.008038578 = product of:
      0.03751336 = sum of:
        0.020922182 = weight(_text_:web in 2404) [ClassicSimilarity], result of:
          0.020922182 = score(doc=2404,freq=2.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.21634221 = fieldWeight in 2404, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=2404)
        0.00856136 = weight(_text_:information in 2404) [ClassicSimilarity], result of:
          0.00856136 = score(doc=2404,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.16457605 = fieldWeight in 2404, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=2404)
        0.008029819 = product of:
          0.024089456 = sum of:
            0.024089456 = weight(_text_:22 in 2404) [ClassicSimilarity], result of:
              0.024089456 = score(doc=2404,freq=2.0), product of:
                0.103770934 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.029633347 = queryNorm
                0.23214069 = fieldWeight in 2404, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2404)
          0.33333334 = coord(1/3)
      0.21428572 = coord(3/14)
    
    Abstract
    Reports on a study of the search tactics used in searching the WWW and in dealing with difficulties such as too many postings and no relevant postings. Describes how the study was carried out, the analytical techniques used in it, and the results. Notes that with regard to tactics used to address search difficulties, no differences were found between searchers for texts and those for graphic information, and between those for known items and subject searches. Comments on the similarities and differences between the tactics used and and those used in online searching, including online catalogue searching
    Date
    25.12.1998 19:22:31
    Footnote
    Part of an issue devoted to electronic resources and their use in libraries, from the viewpoint of reference services, with an emphasis on the Internet and Geographic Information Systems
  12. Xu, Y.; Liu, C.: ¬The dynamics of interactive information retrieval : part II: an empirical study from the activity theory perspective (2007) 0.01
    0.00802995 = product of:
      0.056209646 = sum of:
        0.016016837 = weight(_text_:information in 333) [ClassicSimilarity], result of:
          0.016016837 = score(doc=333,freq=14.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.3078936 = fieldWeight in 333, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=333)
        0.04019281 = weight(_text_:retrieval in 333) [ClassicSimilarity], result of:
          0.04019281 = score(doc=333,freq=10.0), product of:
            0.08963835 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.029633347 = queryNorm
            0.44838852 = fieldWeight in 333, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=333)
      0.14285715 = coord(2/14)
    
    Abstract
    Human information-seeking behavior is complicated. Activity theory is a powerful theoretical instrument to untangle the "complications." Based on activity theory, a comprehensive framework is proposed in Part I (Y. Xu, 2007) of this report to describe interactive information retrieval (IIR) behavior. A set of propositions is also proposed to describe the mechanisms governing users' cognitive activity and the interaction between users' cognitive states and manifested retrieval behavior. An empirical study is carried out to verify the propositions. The authors' experimental simulation of 81 participants in one search session indicates the propositions are largely supported. Their findings indicate IIR behavior is planned. Users adopt a divide-and-conquer strategy in information retrieval. The planning of information retrieval activity is also partially manifested in query revision tactics. Users learn from previously read documents. A user's interaction with a system ultimately changes the user's information need and the resulting relevance judgment, but the dynamics of topicality perception and novelty perception occur at different paces.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.7, S.987-998
  13. English, W.: ¬A short primer in conducting searches (1998) 0.01
    0.0077074226 = product of:
      0.053951956 = sum of:
        0.041844364 = weight(_text_:web in 1669) [ClassicSimilarity], result of:
          0.041844364 = score(doc=1669,freq=2.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.43268442 = fieldWeight in 1669, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.09375 = fieldNorm(doc=1669)
        0.012107591 = weight(_text_:information in 1669) [ClassicSimilarity], result of:
          0.012107591 = score(doc=1669,freq=2.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.23274569 = fieldWeight in 1669, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.09375 = fieldNorm(doc=1669)
      0.14285715 = coord(2/14)
    
    Abstract
    Presents a brief guide to using Boolean operators and search engines to find information on the Web
  14. Spink, A.; Ozmultu, H.C.: Characteristics of question format web queries : an exploratory study (2002) 0.01
    0.007609078 = product of:
      0.053263545 = sum of:
        0.046129078 = weight(_text_:web in 3910) [ClassicSimilarity], result of:
          0.046129078 = score(doc=3910,freq=14.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.47698978 = fieldWeight in 3910, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3910)
        0.0071344664 = weight(_text_:information in 3910) [ClassicSimilarity], result of:
          0.0071344664 = score(doc=3910,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.13714671 = fieldWeight in 3910, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3910)
      0.14285715 = coord(2/14)
    
    Abstract
    Web queries in question format are becoming a common element of a user's interaction with Web search engines. Web search services such as Ask Jeeves - a publicly accessible question and answer (Q&A) search engine - request users to enter question format queries. This paper provides results from a study examining queries in question format submitted to two different Web search engines - Ask Jeeves that explicitly encourages queries in question format and the Excite search service that does not explicitly encourage queries in question format. We identify the characteristics of queries in question format in two different data sets: (1) 30,000 Ask Jeeves queries and 15,575 Excite queries, including the nature, length, and structure of queries in question format. Findings include: (1) 50% of Ask Jeeves queries and less than 1% of Excite were in question format, (2) most users entered only one query in question format with little query reformulation, (3) limited range of formats for queries in question format - mainly "where", "what", or "how" questions, (4) most common question query format was "Where can I find ..." for general information on a topic, and (5) non-question queries may be in request format. Overall, four types of user Web queries were identified: keyword, Boolean, question, and request. These findings provide an initial mapping of the structure and content of queries in question and request format. Implications for Web search services are discussed.
    Source
    Information processing and management. 38(2002) no.4, S.453-471
  15. Jansen, B.J.; Booth, D.L.; Spink, A.: Determining the informational, navigational, and transactional intent of Web queries (2008) 0.01
    0.0075481744 = product of:
      0.05283722 = sum of:
        0.046783425 = weight(_text_:web in 2091) [ClassicSimilarity], result of:
          0.046783425 = score(doc=2091,freq=10.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.48375595 = fieldWeight in 2091, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=2091)
        0.0060537956 = weight(_text_:information in 2091) [ClassicSimilarity], result of:
          0.0060537956 = score(doc=2091,freq=2.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.116372846 = fieldWeight in 2091, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=2091)
      0.14285715 = coord(2/14)
    
    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.
    Source
    Information processing and management. 44(2008) no.3, S.1251-1266
  16. Zhang, Y.: ¬The influence of mental models on undergraduate students' searching behavior on the Web (2008) 0.01
    0.0075481744 = product of:
      0.05283722 = sum of:
        0.046783425 = weight(_text_:web in 2097) [ClassicSimilarity], result of:
          0.046783425 = score(doc=2097,freq=10.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.48375595 = fieldWeight in 2097, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=2097)
        0.0060537956 = weight(_text_:information in 2097) [ClassicSimilarity], result of:
          0.0060537956 = score(doc=2097,freq=2.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.116372846 = fieldWeight in 2097, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=2097)
      0.14285715 = coord(2/14)
    
    Abstract
    This article explores the effects of undergraduate students' mental models of the Web on their online searching behavior. Forty-four undergraduate students, mainly freshmen and sophomores, participated in the study. Subjects' mental models of the Web were treated as equally good styles and operationalized as drawings of their perceptions about the Web. Four types of mental models of the Web were identified based on the drawings and the associated descriptions: technical view, functional view, process view, and connection view. In the study, subjects were required to finish two search tasks. Searching behavior was measured from four aspects: navigation and performance, subjects' feelings about tasks and their own performances, query construction, and search patterns. The four mental model groups showed different navigation and querying behaviors, but the differences were not significant. Subjects' satisfaction with their own performances was found to be significantly correlated with the time to complete the task. The results also showed that the familiarity of the task to subjects had a major effect on their ways to start interaction, query construction, and search patterns.
    Source
    Information processing and management. 44(2008) no.3, S.1330-1345
  17. Jansen, B.J.; Resnick, M.: ¬An examination of searcher's perceptions of nonsponsored and sponsored links during ecommerce Web searching (2006) 0.01
    0.0075424127 = product of:
      0.052796885 = sum of:
        0.042707227 = weight(_text_:web in 221) [ClassicSimilarity], result of:
          0.042707227 = score(doc=221,freq=12.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.4416067 = fieldWeight in 221, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=221)
        0.010089659 = weight(_text_:information in 221) [ClassicSimilarity], result of:
          0.010089659 = score(doc=221,freq=8.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.19395474 = fieldWeight in 221, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=221)
      0.14285715 = coord(2/14)
    
    Abstract
    In this article, we report results of an investigation into the effect of sponsored links on ecommerce information seeking on the Web. In this research, 56 participants each engaged in six ecommerce Web searching tasks. We extracted these tasks from the transaction log of a Web search engine, so they represent actual ecommerce searching information needs. Using 60 organic and 30 sponsored Web links, the quality of the Web search engine results was controlled by switching nonsponsored and sponsored links on half of the tasks for each participant. This allowed for investigating the bias toward sponsored links while controlling for quality of content. The study also investigated the relationship between searching self-efficacy, searching experience, types of ecommerce information needs, and the order of links on the viewing of sponsored links. Data included 2,453 interactions with links from result pages and 961 utterances evaluating these links. The results of the study indicate that there is a strong preference for nonsponsored links, with searchers viewing these results first more than 82% of the time. Searching self-efficacy and experience does not increase the likelihood of viewing sponsored links, and the order of the result listing does not appear to affect searcher evaluation of sponsored links. The implications for sponsored links as a long-term business model are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.14, S.1949-1961
  18. Carrière, J.; Kazman, R.: WebQuery : searching and visualizing the Web through connectivity (1996) 0.01
    0.007475693 = product of:
      0.052329846 = sum of:
        0.041844364 = weight(_text_:web in 2676) [ClassicSimilarity], result of:
          0.041844364 = score(doc=2676,freq=8.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.43268442 = fieldWeight in 2676, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=2676)
        0.0104854815 = weight(_text_:information in 2676) [ClassicSimilarity], result of:
          0.0104854815 = score(doc=2676,freq=6.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.20156369 = fieldWeight in 2676, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=2676)
      0.14285715 = coord(2/14)
    
    Abstract
    Finding information located somewhere on the WWW is an error-prone and frustrating task. The WebQuey system offers a powerful new method for searching the Web based on connectivity and content. We do this by examining links among the nodes returned in a keyword-based query. We then rank the nodes, giving the highest rank to the most highly connected nodes. By doing so, we are finding 'hot spots' on the Web that contain onformation germane to a user's query. WebQuery not only ranks and filters the results of a Web query, it also extends the result set beyond what the search engine retrieves, by finding 'interesting' sites that are hoghly connected to those sites returned by the original query. Even with WebQuery filtering and ranking query results, the result sets can be enourmous. So, wen need to visualize the returned information. We explore several techniques for visualizing this information - including cone trees, 2D graphs, 3D graphy, lists, and bullseyes - and discuss the criteria for using each of the techniques
  19. Wang, P.; Berry, M.W.; Yang, Y.: Mining longitudinal Web queries : trends and patterns (2003) 0.01
    0.0074666077 = product of:
      0.05226625 = sum of:
        0.042278 = weight(_text_:web in 6561) [ClassicSimilarity], result of:
          0.042278 = score(doc=6561,freq=6.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.43716836 = fieldWeight in 6561, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6561)
        0.009988253 = weight(_text_:information in 6561) [ClassicSimilarity], result of:
          0.009988253 = score(doc=6561,freq=4.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.1920054 = fieldWeight in 6561, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6561)
      0.14285715 = coord(2/14)
    
    Abstract
    This project analyzed 541,920 user queries submitted to and executed in an academic Website during a four-year period (May 1997 to May 2001) using a relational database. The purpose of the study is three-fold: (1) to understand Web users' query behavior; (2) to identify problems encountered by these Web users; (3) to develop appropriate techniques for optimization of query analysis and mining. The linguistic analyses focus an query structures, lexicon, and word associations using statistical measures such as Zipf distribution and mutual information. A data model with finest granularity is used for data storage and iterative analyses. Patterns and trends of querying behavior are identified and compared with previous studies.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.8, S.743-758
  20. Mansourian, I.: Web search efficacy : definition and implementation (2008) 0.01
    0.0073105586 = product of:
      0.051173907 = sum of:
        0.046129078 = weight(_text_:web in 2565) [ClassicSimilarity], result of:
          0.046129078 = score(doc=2565,freq=14.0), product of:
            0.09670874 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.029633347 = queryNorm
            0.47698978 = fieldWeight in 2565, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2565)
        0.0050448296 = weight(_text_:information in 2565) [ClassicSimilarity], result of:
          0.0050448296 = score(doc=2565,freq=2.0), product of:
            0.052020688 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.029633347 = queryNorm
            0.09697737 = fieldWeight in 2565, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2565)
      0.14285715 = coord(2/14)
    
    Abstract
    Purpose - This paper aims to report a number of factors that are perceived by web users as influential elements in their search procedure. The paper introduces a new conceptual measure called "web search efficacy" (hereafter WSE) to evaluate the performance of searches mainly based on users' perceptions. Design/methodology/approach - A rich dataset of a wider study was inductively re-explored to identify different categories that are perceived influential by web users on the final outcome of their searches. A selective review of the literature was carried out to discover to what extent previous research supports the findings of the current study. Findings - The analysis of the dataset led to the identification of five categories of influential factors. Within each group different factors have been recognized. Accordingly, the concept of WSE has been introduced. The five "Ss" which determine WSE are searcher's performance, search tool's performance, search strategy, search topic, and search situation. Research limitations/implications - The research body is scattered in different areas and it is difficult to carry out a comprehensive review. The WSE table, which is derived from the empirical data and was supported by previous research, can be employed for further research in various groups of web users. Originality/value - The paper contributes to the area of information seeking on the web by providing researchers with a new conceptual framework to evaluate the efficiency of each search session and identify the underlying factors on the final outcome of web searching.

Languages

  • e 262
  • d 5
  • ja 1
  • slv 1
  • More… Less…

Types

  • a 258
  • m 10
  • el 2
  • s 1
  • More… Less…