Search (26 results, page 1 of 2)

0.0666874 = product of:
  0.16671848 = sum of:
    0.06845724 = weight(_text_:wide in 245) [ClassicSimilarity], result of:
      0.06845724 = score(doc=245,freq=2.0), product of:
        0.19977365 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.045087915 = queryNorm
        0.342674 = fieldWeight in 245, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.0546875 = fieldNorm(doc=245)
    0.09826125 = weight(_text_:web in 245) [ClassicSimilarity], result of:
      0.09826125 = score(doc=245,freq=14.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.6677857 = fieldWeight in 245, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0546875 = fieldNorm(doc=245)
  0.4 = coord(2/5)

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

0.045551278 = product of:
  0.11387819 = sum of:
    0.048898023 = weight(_text_:wide in 5229) [ClassicSimilarity], result of:
      0.048898023 = score(doc=5229,freq=2.0), product of:
        0.19977365 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.045087915 = queryNorm
        0.24476713 = fieldWeight in 5229, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5229)
    0.064980164 = weight(_text_:web in 5229) [ClassicSimilarity], result of:
      0.064980164 = score(doc=5229,freq=12.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.4416067 = fieldWeight in 5229, 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=5229)
  0.4 = coord(2/5)

Abstract

Thirty-one patrons, who were selected by Slone to provide a range of age and experience, agreed when approached while using the catalog of the Wake County library system to try searching via the Internet. Fifteen searched the Wake County online catalog in this manner and 16 searched the World Wide Web, including that catalog. They were subjected to brief pre-structured taped interviews before and after their searches and observed during the searching process resulting in a log of behaviors, comments, pages accessed, and time spent. Data were analyzed across participants and categories. Web searches were characterized as linking, URL, search engine, within a site domain, and searching a web catalog; and participants by the number of these techniques used. Four used only one, 13 used two, 11 used three, two used four, and one all five. Participant experience was characterized as never used, used search engines, browsing experience, email experience, URL experience, catalog experience, and finally chat room/newsgroup experience. Sixteen percent of the participants had never used the Internet, 71% had used search engines, 65% had browsed, 58% had used email, 39% had used URLs, 39% had used online catalogs, and 32% had used chat rooms. The catalog was normally consulted before the web, where both were used, and experience with an online catalog assists in web use. Scrolling was found to be unpopular and practiced halfheartedly.

0.030170426 = product of:
  0.075426064 = sum of:
    0.048898023 = weight(_text_:wide in 5170) [ClassicSimilarity], result of:
      0.048898023 = score(doc=5170,freq=2.0), product of:
        0.19977365 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.045087915 = queryNorm
        0.24476713 = fieldWeight in 5170, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5170)
    0.026528042 = weight(_text_:web in 5170) [ClassicSimilarity], result of:
      0.026528042 = score(doc=5170,freq=2.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.18028519 = fieldWeight in 5170, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5170)
  0.4 = coord(2/5)

Abstract

Meho and Tibbo show that the Ellis model of information seeking applies to a web environment by way of a replication of his study in this case using behavior of social science faculty studying stateless nations, a group diverse in skills, origins, and research specialities. Data were collected by way of e-mail interviews. Material on stateless nations was limited to papers in English on social science topics published between 1998 and 2000. Of these 251 had 212 unique authors identified as academic scholars and had sufficient information to provide e-mail addresses. Of the 139 whose addresses were located, 9 who were physically close were reserved for face to face interviews, and of the remainder 60 agreed to participate and responded to the 25 open ended question interview. Follow up questions generated a 75% response. Of the possible face to face interviews five agreed to participate and provided 26 thousand words as opposed to 69 thousand by the 45 e-mail participants. The activities of the Ellis model are confirmed but four additional activities are also identified. These are accessing, i.e. finding the material identified in indirect sources of information; networking, or the maintaining of close contacts with a wide range of colleagues and other human sources; verifying, i.e. checking the accuracy of new information; and information managing, the filing and organizing of collected information. All activities are grouped into four stages searching, accessing, processing, and ending.

0.016609183 = product of:
  0.08304591 = sum of:
    0.08304591 = weight(_text_:web in 2277) [ClassicSimilarity], result of:
      0.08304591 = score(doc=2277,freq=10.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.5643819 = fieldWeight in 2277, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2277)
  0.2 = coord(1/5)

Abstract

This article reviews studies, conducted between 1995 and 2000, on Web search behavior. These studies reported on children as well as on adults. Most of the studies on children described their interaction with the Web. Research on adult searchers focused on describing search patterns, and many studies investigated effects of selected factors on search behavior, including information organization and presentation, type of search task, Web experience, cognitive abilities, and affective states. What distinguishes the research on adult searchers is the use of multiple data-gathering methods. The research on Web search behavior reflects researchers' commitment to examine users in their information environment and exhibits rigor in design and data analysis. However, many studies lack external validity. Implications of this body of research are discussed.

0.015006527 = product of:
  0.07503264 = sum of:
    0.07503264 = weight(_text_:web in 600) [ClassicSimilarity], result of:
      0.07503264 = score(doc=600,freq=16.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.5099235 = fieldWeight in 600, 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=600)
  0.2 = coord(1/5)

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.

0.015006527 = product of:
  0.07503264 = sum of:
    0.07503264 = weight(_text_:web in 335) [ClassicSimilarity], result of:
      0.07503264 = score(doc=335,freq=16.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = 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)
  0.2 = coord(1/5)

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.

0.014855704 = product of:
  0.07427852 = sum of:
    0.07427852 = weight(_text_:web in 891) [ClassicSimilarity], result of:
      0.07427852 = score(doc=891,freq=8.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = 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)
  0.2 = coord(1/5)

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.

0.014236443 = product of:
  0.07118221 = sum of:
    0.07118221 = weight(_text_:web in 2091) [ClassicSimilarity], result of:
      0.07118221 = score(doc=2091,freq=10.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = 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)
  0.2 = coord(1/5)

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.

0.014236443 = product of:
  0.07118221 = sum of:
    0.07118221 = weight(_text_:web in 2097) [ClassicSimilarity], result of:
      0.07118221 = score(doc=2097,freq=10.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = 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)
  0.2 = coord(1/5)

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.

0.014037321 = product of:
  0.07018661 = sum of:
    0.07018661 = weight(_text_:web in 587) [ClassicSimilarity], result of:
      0.07018661 = score(doc=587,freq=14.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.47698978 = fieldWeight in 587, 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=587)
  0.2 = coord(1/5)

Abstract

Subject content analysis of Web query terms is essential to understand Web searching interests. Such analysis includes exploring search topics and observing changes in their frequency distributions with time. To provide a basis for in-depth analysis of users' search interests on a larger scale, this article presents a query categorization approach to automatically classifying Web query terms into broad subject categories. Because a query is short in length and simple in structure, its intended subject(s) of search is difficult to judge. Our approach, therefore, combines the search processes of real-world search engines to obtain highly ranked Web documents based on each unknown query term. These documents are used to extract cooccurring terms and to create a feature set. An effective ranking function has also been developed to find the most appropriate categories. Three search engine logs in Taiwan were collected and tested. They contained over 5 million queries from different periods of time. The achieved performance is quite encouraging compared with that of human categorization. The experimental results demonstrate that the approach is efficient in dealing with large numbers of queries and adaptable to the dynamic Web environment. Through good integration of human and machine efforts, the frequency distributions of subject categories in response to changes in users' search interests can be systematically observed in real time. The approach has also shown potential for use in various information retrieval applications, and provides a basis for further Web searching studies.

0.012996033 = product of:
  0.064980164 = sum of:
    0.064980164 = weight(_text_:web in 221) [ClassicSimilarity], result of:
      0.064980164 = score(doc=221,freq=12.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = 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)
  0.2 = coord(1/5)

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.

0.012865419 = product of:
  0.06432709 = sum of:
    0.06432709 = weight(_text_:web in 6561) [ClassicSimilarity], result of:
      0.06432709 = score(doc=6561,freq=6.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = 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)
  0.2 = coord(1/5)

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.

0.0127334595 = product of:
  0.0636673 = sum of:
    0.0636673 = weight(_text_:web in 991) [ClassicSimilarity], result of:
      0.0636673 = score(doc=991,freq=8.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.43268442 = fieldWeight in 991, 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=991)
  0.2 = coord(1/5)

Abstract

Multitasking is the human ability to handle the demands of multiple tasks. Multitasking behavior involves the ordering of multiple tasks and switching between tasks. People often multitask when using information retrieval (IR) technologies as they seek information on more than one information problem over single or multiple search episodes. However, limited studies have examined how people order their information problems, especially during their Web search engine interaction. The aim of our exploratory study was to investigate assigned information problem ordering by forty (40) study participants engaged in Web search. Findings suggest that assigned information problem ordering was influenced by the following factors, including personal interest, problem knowledge, perceived level of information available on the Web, ease of finding information, level of importance and seeking information on information problems in order from general to specific. Personal interest and problem knowledge were the major factors during assigned information problem ordering. Implications of the findings and further research are discussed. The relationship between information problem ordering and gratification theory is an important area for further exploration.

0.0127334595 = product of:
  0.0636673 = sum of:
    0.0636673 = weight(_text_:web in 2936) [ClassicSimilarity], result of:
      0.0636673 = score(doc=2936,freq=8.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.43268442 = fieldWeight in 2936, 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=2936)
  0.2 = coord(1/5)

Abstract

Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation state to another to predict their next state. We developed first-, second-, third-, and fourth-order models and evaluated each model for accuracy of prediction, coverage of the dataset, and complexity of the possible pattern set. The results show that Reformulation and Assistance account for approximately 45% of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40% overall and higher than 70% for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance.

0.011863702 = product of:
  0.05931851 = sum of:
    0.05931851 = weight(_text_:web in 1081) [ClassicSimilarity], result of:
      0.05931851 = score(doc=1081,freq=10.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.40312994 = fieldWeight in 1081, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1081)
  0.2 = coord(1/5)

Abstract

The aim of the work described in this paper is to evaluate the influencing effects of query-biased summaries in web searching. For this purpose, a summarisation system has been developed, and a summary tailored to the user's query is generated automatically for each document retrieved. The system aims to provide both a better means of assessing document relevance than titles or abstracts typical of many web search result lists. Through visiting each result page at retrieval-time, the system provides the user with an idea of the current page content and thus deals with the dynamic nature of the web. To examine the effectiveness of this approach, a task-oriented, comparative evaluation between four different web retrieval systems was performed; two that use query-biased summarisation, and two that use the standard ranked titles/abstracts approach. The results from the evaluation indicate that query-biased summarisation techniques appear to be more useful and effective in helping users gauge document relevance than the traditional ranked titles/abstracts approach. The same methodology was used to compare the effectiveness of two of the web's major search engines; AltaVista and Google.

0.011027501 = product of:
  0.055137504 = sum of:
    0.055137504 = weight(_text_:web in 3475) [ClassicSimilarity], result of:
      0.055137504 = score(doc=3475,freq=6.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.37471575 = fieldWeight in 3475, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=3475)
  0.2 = coord(1/5)

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.

0.011027501 = product of:
  0.055137504 = sum of:
    0.055137504 = weight(_text_:web in 4472) [ClassicSimilarity], result of:
      0.055137504 = score(doc=4472,freq=6.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.37471575 = fieldWeight in 4472, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=4472)
  0.2 = coord(1/5)

Abstract

This paper reports the results of a study funded by the Arts and Humanities Research Board which sought to investigate links between Web search strategies and retrieval effectiveness. A total of 68 students, enrolled on masters programmes in librarianship, information management and information systems, searched for two topics using the AltaVista search engine. Logs of the resultant 341 queries, along with relevance judgements for over 4,000 retrieved items, were analysed using factor analysis and regression. The differing but complementary types and strengths of evidence produced by these two forms of analysis are discussed and presented. Retrieval effectiveness was associated positively with best-match searching and negatively with Boolean searching. The implications of these findings for Web searching are discussed.

0.010611217 = product of:
  0.053056084 = sum of:
    0.053056084 = weight(_text_:web in 3539) [ClassicSimilarity], result of:
      0.053056084 = score(doc=3539,freq=2.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.36057037 = fieldWeight in 3539, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.078125 = fieldNorm(doc=3539)
  0.2 = coord(1/5)

0.009779605 = product of:
  0.048898023 = sum of:
    0.048898023 = weight(_text_:wide in 1713) [ClassicSimilarity], result of:
      0.048898023 = score(doc=1713,freq=2.0), product of:
        0.19977365 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.045087915 = queryNorm
        0.24476713 = fieldWeight in 1713, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1713)
  0.2 = coord(1/5)

Abstract

User studies demonstrate that nondomain experts do not use the same information-seeking strategies as domain experts. Because of the transformation of integrated library systems into Information Gateways in the late 1990s, both nondomain experts and domain experts have had available to them the wide range of information-seeking strategies in a single system. This article describes the results of a study to answer three research questions: (1) do nondomain experts enlist the strategies of domain experts? (2) if they do, how did they learn about these strategies? and (3) are they successful using them? Interviews, audio recordings, screen captures, and observations were used to gather data from 14 undergraduate students who searched an academic library's Information Gateway. The few times that the undergraduates in this study enlisted search strategies that were characteristic of domain experts, it usually took perseverance, trial-and-error, serendipity, or a combination of all three for them to find useful information. Although this study's results provide no compelling reasons for systems to support features that make domain-expert strategies possible, there is need for system features that scaffold nondomain experts from their usual strategies to the strategies characteristic of domain experts.

0.009003917 = product of:
  0.045019582 = sum of:
    0.045019582 = weight(_text_:web in 3476) [ClassicSimilarity], result of:
      0.045019582 = score(doc=3476,freq=4.0), product of:
        0.14714488 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.045087915 = queryNorm
        0.3059541 = fieldWeight in 3476, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=3476)
  0.2 = coord(1/5)

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.