Search (174 results, page 1 of 9)

0.036995452 = product of:
  0.12948407 = sum of:
    0.1047525 = weight(_text_:interactions in 3265) [ClassicSimilarity], result of:
      0.1047525 = score(doc=3265,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.4561343 = fieldWeight in 3265, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3265)
    0.024731567 = weight(_text_:with in 3265) [ClassicSimilarity], result of:
      0.024731567 = score(doc=3265,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.2635687 = fieldWeight in 3265, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3265)
  0.2857143 = coord(2/7)

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

0.03523018 = product of:
  0.12330562 = sum of:
    0.08978786 = weight(_text_:interactions in 5240) [ClassicSimilarity], result of:
      0.08978786 = score(doc=5240,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.39097226 = fieldWeight in 5240, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.046875 = fieldNorm(doc=5240)
    0.03351775 = weight(_text_:with in 5240) [ClassicSimilarity], result of:
      0.03351775 = score(doc=5240,freq=10.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.35720462 = fieldWeight in 5240, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.046875 = fieldNorm(doc=5240)
  0.2857143 = coord(2/7)

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.

0.03492582 = product of:
  0.122240365 = sum of:
    0.1047525 = weight(_text_:interactions in 199) [ClassicSimilarity], result of:
      0.1047525 = score(doc=199,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.4561343 = fieldWeight in 199, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0546875 = fieldNorm(doc=199)
    0.017487857 = weight(_text_:with in 199) [ClassicSimilarity], result of:
      0.017487857 = score(doc=199,freq=2.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.1863712 = fieldWeight in 199, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0546875 = fieldNorm(doc=199)
  0.2857143 = coord(2/7)

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

0.0338021 = product of:
  0.118307345 = sum of:
    0.105816014 = weight(_text_:interactions in 300) [ClassicSimilarity], result of:
      0.105816014 = score(doc=300,freq=4.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.4607652 = fieldWeight in 300, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=300)
    0.012491328 = weight(_text_:with in 300) [ClassicSimilarity], result of:
      0.012491328 = score(doc=300,freq=2.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.1331223 = fieldWeight in 300, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=300)
  0.2857143 = coord(2/7)

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

0.0338021 = product of:
  0.118307345 = sum of:
    0.105816014 = weight(_text_:interactions in 301) [ClassicSimilarity], result of:
      0.105816014 = score(doc=301,freq=4.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.4607652 = fieldWeight in 301, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=301)
    0.012491328 = weight(_text_:with in 301) [ClassicSimilarity], result of:
      0.012491328 = score(doc=301,freq=2.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.1331223 = fieldWeight in 301, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=301)
  0.2857143 = coord(2/7)

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

0.031710386 = product of:
  0.11098635 = sum of:
    0.08978786 = weight(_text_:interactions in 5085) [ClassicSimilarity], result of:
      0.08978786 = score(doc=5085,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.39097226 = fieldWeight in 5085, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.046875 = fieldNorm(doc=5085)
    0.021198487 = weight(_text_:with in 5085) [ClassicSimilarity], result of:
      0.021198487 = score(doc=5085,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.22591603 = fieldWeight in 5085, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.046875 = fieldNorm(doc=5085)
  0.2857143 = coord(2/7)

Abstract

The purpose of this analysis was to evaluate an existing set of search tasks in terms of their effectiveness as part of a "shared infrastructure" for conducting interactive IR research. Twenty search tasks that varied in their cognitive complexity and domain were assigned to 47 study participants; the 3,101 moves used to complete those tasks were then analyzed in terms of frequency of each type of move and the sequential patterns they formed. The cognitive complexity of the tasks influenced the number of moves used to complete the tasks, with the most complex (i.e., Create) tasks requiring more moves than tasks at other levels of complexity. Across the four domains, the Commerce tasks elicited more search moves per search. When sequences of moves were analyzed, seven patterns were identified; some of these patterns were associated with particular task characteristics. The findings suggest that search tasks can be designed to elicit particular types of search behaviors and, thus, allow researchers to focus attention on particular aspects of IR interactions.

0.029284675 = product of:
  0.102496356 = sum of:
    0.017665405 = weight(_text_:with in 4915) [ClassicSimilarity], result of:
      0.017665405 = score(doc=4915,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.18826336 = fieldWeight in 4915, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4915)
    0.08483095 = product of:
      0.1696619 = sum of:
        0.1696619 = weight(_text_:humans in 4915) [ClassicSimilarity], result of:
          0.1696619 = score(doc=4915,freq=6.0), product of:
            0.26276368 = queryWeight, product of:
              6.7481275 = idf(docFreq=140, maxDocs=44218)
              0.038938753 = queryNorm
            0.64568245 = fieldWeight in 4915, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              6.7481275 = idf(docFreq=140, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4915)
      0.5 = coord(1/2)
  0.2857143 = coord(2/7)

Abstract

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

0.028515965 = product of:
  0.09980587 = sum of:
    0.074823216 = weight(_text_:interactions in 3825) [ClassicSimilarity], result of:
      0.074823216 = score(doc=3825,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.3258102 = fieldWeight in 3825, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3825)
    0.024982655 = weight(_text_:with in 3825) [ClassicSimilarity], result of:
      0.024982655 = score(doc=3825,freq=8.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.2662446 = fieldWeight in 3825, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3825)
  0.2857143 = coord(2/7)

Abstract

In this study, we evaluated the ability of computational cognitive models of web-navigation like CoLiDeS and CoLiDeS+ to model i) user interactions with search engines and ii) individual differences in search behavior due to variations in cognitive factors such as aging. CoLiDeS and CoLiDeS+ were extended to predict user clicks on search engine result pages. Their performance was evaluated using actual behavioral data from an experiment in which 2 types of information search tasks (simple vs. difficult), were presented to younger and older participants. The results showed that the model predictions matched significantly better with the actual user behavior on difficult tasks compared to simple tasks and with younger participants compared to older participants, especially for difficult tasks. Also, the matches were significantly better with CoLiDeS+ compared to CoLiDeS, especially for difficult tasks. We conclude that the advanced capabilities of CoLiDeS+, such as incorporating contextual information and implementing backtracking strategies enable it to predict user behavior significantly better than CoLiDeS, especially on difficult tasks. The usefulness of these modeling outcomes for the design of support systems for older adults is discussed.

0.027559668 = product of:
  0.09645883 = sum of:
    0.074823216 = weight(_text_:interactions in 307) [ClassicSimilarity], result of:
      0.074823216 = score(doc=307,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.3258102 = fieldWeight in 307, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=307)
    0.021635616 = weight(_text_:with in 307) [ClassicSimilarity], result of:
      0.021635616 = score(doc=307,freq=6.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.2305746 = fieldWeight in 307, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=307)
  0.2857143 = coord(2/7)

Abstract

This is the first study that compares types of orientation tactics that blind and sighted users applied in their initial interactions with a digital library (DL) and the associated factors. Multiple methods were employed for data collection: questionnaires, think-aloud protocols, and transaction logs. The paper identifies seven types of orientation tactics applied by the two groups of users. While sighted users focused on skimming DL content, blind users concentrated on exploring DL structure. Moreover, the authors discovered 13 types of system, user, and interaction factors that led to the use of orientation tactics. More system factors than user factors affect blind users' tactics in browsing DL structures. The findings of this study support the social model that the sight-centered design of DLs, rather than blind users' disability, prohibits them from effectively interacting with a DL. Simultaneously, the results reveal the limitation of existing interactive information retrieval models that do not take people with disabilities into consideration. DL design implications are discussed based on the identified factors.

0.02642532 = product of:
  0.09248862 = sum of:
    0.074823216 = weight(_text_:interactions in 221) [ClassicSimilarity], result of:
      0.074823216 = score(doc=221,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.3258102 = fieldWeight in 221, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=221)
    0.017665405 = weight(_text_:with in 221) [ClassicSimilarity], result of:
      0.017665405 = score(doc=221,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.18826336 = fieldWeight in 221, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=221)
  0.2857143 = coord(2/7)

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.

0.02642532 = product of:
  0.09248862 = sum of:
    0.074823216 = weight(_text_:interactions in 3623) [ClassicSimilarity], result of:
      0.074823216 = score(doc=3623,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.3258102 = fieldWeight in 3623, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3623)
    0.017665405 = weight(_text_:with in 3623) [ClassicSimilarity], result of:
      0.017665405 = score(doc=3623,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.18826336 = fieldWeight in 3623, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3623)
  0.2857143 = coord(2/7)

Abstract

Purpose - This paper aims to report findings from an exploratory study investigating the web interactions and technoliteracy of children in the early childhood years. Previous research has studied aspects of older children's technoliteracy and web searching; however, few studies have analyzed web search data from children younger than six years of age. Design/methodology/approach - The study explored the Google web searching and technoliteracy of young children who are enrolled in a "preparatory classroom" or kindergarten (the year before young children begin compulsory schooling in Queensland, Australia). Young children were video- and audio-taped while conducting Google web searches in the classroom. The data were qualitatively analysed to understand the young children's web search behaviour. Findings - The findings show that young children engage in complex web searches, including keyword searching and browsing, query formulation and reformulation, relevance judgments, successive searches, information multitasking and collaborative behaviours. The study results provide significant initial insights into young children's web searching and technoliteracy. Practical implications - The use of web search engines by young children is an important research area with implications for educators and web technologies developers. Originality/value - This is the first study of young children's interaction with a web search engine.

0.02642532 = product of:
  0.09248862 = sum of:
    0.074823216 = weight(_text_:interactions in 1824) [ClassicSimilarity], result of:
      0.074823216 = score(doc=1824,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.3258102 = fieldWeight in 1824, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1824)
    0.017665405 = weight(_text_:with in 1824) [ClassicSimilarity], result of:
      0.017665405 = score(doc=1824,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.18826336 = fieldWeight in 1824, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1824)
  0.2857143 = coord(2/7)

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.

0.021140257 = product of:
  0.0739909 = sum of:
    0.059858575 = weight(_text_:interactions in 971) [ClassicSimilarity], result of:
      0.059858575 = score(doc=971,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.26064816 = fieldWeight in 971, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.03125 = fieldNorm(doc=971)
    0.014132325 = weight(_text_:with in 971) [ClassicSimilarity], result of:
      0.014132325 = score(doc=971,freq=4.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.15061069 = fieldWeight in 971, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.03125 = fieldNorm(doc=971)
  0.2857143 = coord(2/7)

Abstract

Though much information behaviour takes place in collaborative settings, information behaviour processes are commonly perceived and modelled by information scientists as individual processes. The paper presents and discusses the findings from a qualitative preliminary case study exploring Kuhlthau's Information Search Process (ISP) model in a group-based educational setting. The aim of the study was to explore if members of a group behave differently from the individual modelled in the ISP model and further, if members of a group demonstrate different behaviours or they will assimilate and turn the group into 'an individual', just in another sense. During a project assignment, which lasted seven weeks, two groups of information science students filled out a questionnaire and kept diaries of their activities and information-related behaviour. Further, the students were interviewed three times each during the study. It was found that contextual and social factors seem to affect group members' physical activities and their cognitive and emotional experiences during a project assignment with relevance to information behaviour. Though group members to some extent demonstrated similar cognitive experiences as the individual in the ISP model, these experiences did not only result from information seeking activities but also from work task activities and intragroup interactions. Regarding group members' emotional experiences, no emotional 'turning point' resulting in certainty and relief by the end of the information seeking process was identified. Further, some of the group members still felt uncertain, frustrated and disappointed at the end of the project assignment, which partly was associated with a mis-match in motivations, ambitions and project focus among group members. Regarding the intragroup behaviour, group members did not demonstrate similar behaviours, meaning that 'groups' cannot be perceived or modelled as 'an individual', just in another sense. Groups consist of individuals engaged in and affected by a collaborative problem solving process involving information (seeking) behaviour. A natural extension of the ISP model in relation to group processes is suggested, addressing also the impact of social and contextual factors on the individual's information behaviour.

0.017562427 = product of:
  0.06146849 = sum of:
    0.012491328 = weight(_text_:with in 600) [ClassicSimilarity], result of:
      0.012491328 = score(doc=600,freq=2.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.1331223 = fieldWeight in 600, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=600)
    0.048977163 = product of:
      0.097954325 = sum of:
        0.097954325 = weight(_text_:humans in 600) [ClassicSimilarity], result of:
          0.097954325 = score(doc=600,freq=2.0), product of:
            0.26276368 = queryWeight, product of:
              6.7481275 = idf(docFreq=140, maxDocs=44218)
              0.038938753 = queryNorm
            0.37278488 = fieldWeight in 600, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.7481275 = idf(docFreq=140, maxDocs=44218)
              0.0390625 = fieldNorm(doc=600)
      0.5 = coord(1/2)
  0.2857143 = coord(2/7)

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.

0.01710245 = product of:
  0.11971715 = sum of:
    0.11971715 = weight(_text_:interactions in 4520) [ClassicSimilarity], result of:
      0.11971715 = score(doc=4520,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.5212963 = fieldWeight in 4520, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0625 = fieldNorm(doc=4520)
  0.14285715 = coord(1/7)

Abstract

Numerous computer networks worldwide implement the same suite of Transmission Control Protocol / Internet Protocol (TCP/IP) communications rules. These facilitate electronic interactions among remotely situated users. presents a model curriculum designed to introduce newcomers to the Internet in science and technlogy oriented organizations

0.014049942 = product of:
  0.049174793 = sum of:
    0.009993061 = weight(_text_:with in 1264) [ClassicSimilarity], result of:
      0.009993061 = score(doc=1264,freq=2.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.10649783 = fieldWeight in 1264, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.03125 = fieldNorm(doc=1264)
    0.03918173 = product of:
      0.07836346 = sum of:
        0.07836346 = weight(_text_:humans in 1264) [ClassicSimilarity], result of:
          0.07836346 = score(doc=1264,freq=2.0), product of:
            0.26276368 = queryWeight, product of:
              6.7481275 = idf(docFreq=140, maxDocs=44218)
              0.038938753 = queryNorm
            0.2982279 = fieldWeight in 1264, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.7481275 = idf(docFreq=140, maxDocs=44218)
              0.03125 = fieldNorm(doc=1264)
      0.5 = coord(1/2)
  0.2857143 = coord(2/7)

Abstract

Over the past decade, the volume of information available digitally over the Internet has grown enormously. Technical developments in the area of search, such as Google's Page Rank algorithm, have proved so good at serving relevant results that Internet search has become integrated into daily human activity. One can endlessly explore topics of interest simply by querying and reading through the resulting links. Yet, although search engines are well known for providing relevant results based on users' queries, users do not always receive the results they are looking for. Google's Director of Research describes clickstream evidence of frustrated users repeatedly reformulating queries and searching through page after page of results. Given the general quality of search engine results, one must consider the possibility that the frustrated user's query is not effective; that is, it does not describe the essence of the user's interest. Indeed, extensive research into human search behavior has found that humans are not very effective at formulating good search queries that describe what they are interested in. Ideally, the user should simply point to a portion of text that sparked the user's interest, and a system should automatically formulate a search query that captures the essence of the text. In this paper, we describe an implemented system that provides this capability. We first describe how our work differs from existing work in automatic query formulation, and propose a new method for improved quantification of the relevance of candidate search terms drawn from input text using phrase-level analysis. We then propose an implementable method designed to provide relevant queries based on a user's text input. We demonstrate the quality of our results and performance of our system through experimental studies. Our results demonstrate that our system produces relevant search terms with roughly two-thirds precision and recall compared to search terms selected by experts, and that typical users find significantly more relevant results (31% more relevant) more quickly (64% faster) using our system than self-formulated search queries. Further, we show that our implementation can scale to request loads of up to 10 requests per second within current online responsiveness expectations (<2-second response times at the highest loads tested).

0.0128268385 = product of:
  0.08978786 = sum of:
    0.08978786 = weight(_text_:interactions in 1662) [ClassicSimilarity], result of:
      0.08978786 = score(doc=1662,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.39097226 = fieldWeight in 1662, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.046875 = fieldNorm(doc=1662)
  0.14285715 = coord(1/7)

0.011939922 = product of:
  0.041789725 = sum of:
    0.025962738 = weight(_text_:with in 2404) [ClassicSimilarity], result of:
      0.025962738 = score(doc=2404,freq=6.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.2766895 = fieldWeight in 2404, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.046875 = fieldNorm(doc=2404)
    0.015826989 = product of:
      0.031653978 = sum of:
        0.031653978 = weight(_text_:22 in 2404) [ClassicSimilarity], result of:
          0.031653978 = score(doc=2404,freq=2.0), product of:
            0.13635688 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.038938753 = 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)
      0.5 = coord(1/2)
  0.2857143 = coord(2/7)

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

0.010689031 = product of:
  0.074823216 = sum of:
    0.074823216 = weight(_text_:interactions in 4362) [ClassicSimilarity], result of:
      0.074823216 = score(doc=4362,freq=2.0), product of:
        0.22965278 = queryWeight, product of:
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.038938753 = queryNorm
        0.3258102 = fieldWeight in 4362, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.8977947 = idf(docFreq=329, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4362)
  0.14285715 = coord(1/7)

Abstract

Existing methods for automatically analyzing search logs describe search behavior on the basis of syntactic differences (overlapping terms) between queries. Although these analyses provide valuable insights into the complexity and successfulness of search interactions, they offer a limited interpretation of the observed searching behavior, as they do not consider the semantics of users' queries. In this article we propose a method to exploit semantic information in the form of linked data to enrich search queries so as to determine the semantic types of the queries and the relations between queries that are consecutively entered in a search session. This work provides also an in-depth analysis of the search logs of professional users searching a commercial picture portal. Compared to previous image search log analyses, in particular those of professional users, we consider a much larger dataset. We analyze the logs both in a syntactic way and using the proposed semantic approach and compare the results. Our findings show the benefits of using semantics for search log analysis: the identified types of query modifications cannot be appropriately analyzed by only considering term overlap, since queries related in the most frequent ways do not usually share terms.

0.009949936 = product of:
  0.034824774 = sum of:
    0.021635616 = weight(_text_:with in 3340) [ClassicSimilarity], result of:
      0.021635616 = score(doc=3340,freq=6.0), product of:
        0.09383348 = queryWeight, product of:
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.038938753 = queryNorm
        0.2305746 = fieldWeight in 3340, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.409771 = idf(docFreq=10797, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3340)
    0.013189158 = product of:
      0.026378317 = sum of:
        0.026378317 = weight(_text_:22 in 3340) [ClassicSimilarity], result of:
          0.026378317 = score(doc=3340,freq=2.0), product of:
            0.13635688 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.038938753 = queryNorm
            0.19345059 = fieldWeight in 3340, 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=3340)
      0.5 = coord(1/2)
  0.2857143 = coord(2/7)

Abstract

Keeping up to date with research developments is a central activity of academic researchers, but researchers face difficulties in managing the rapid growth of available scientific information. This study examined how researchers stay up to date, using the information journey model as a framework for analysis and investigating which dimensions influence information behaviors. We designed a 2-round study involving semistructured interviews and prototype testing with 61 researchers with 3 levels of seniority (PhD student to professor). Data were analyzed following a semistructured qualitative approach. Five key dimensions that influence information behaviors were identified: level of seniority, information sources, state of the project, level of familiarity, and how well defined the relevant community is. These dimensions are interrelated and their values determine the flow of the information journey. Across all levels of professional expertise, researchers used similar hard (formal) sources to access content, while soft (interpersonal) sources were used to filter information. An important "pain point" that future information tools should address is helping researchers filter information at the point of need.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.1, S.22-35