Search (70 results, page 4 of 4)

0.0026467475 = product of:
  0.007940242 = sum of:
    0.007940242 = product of:
      0.015880484 = sum of:
        0.015880484 = weight(_text_:of in 2038) [ClassicSimilarity], result of:
          0.015880484 = score(doc=2038,freq=10.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.23179851 = fieldWeight in 2038, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=2038)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Web search engines are beginning to offer access to multimedia searching, including audio, video and image searching. In this paper we report findings from a study examining the state of multimedia search functionality on major general and specialized Web search engines. We investigated 102 Web search engines to examine: (1) how many Web search engines offer multimedia searching, (2) the type of multimedia search functionality and methods offered, such as "query by example", and (3) the supports for personalization or customization which are accessible as advanced search. Findings include: (1) few major Web search engines offer multimedia searching and (2) multimedia Web search functionality is generally limited. Our findings show that despite the increasing level of interest in multimedia Web search, those few Web search engines offering multimedia Web search, provide limited multimedia search functionality. Keywords are still the only means of multimedia retrieval, while other methods such as "query by example" are offered by less than 1% of Web search engines examined.

0.002609728 = product of:
  0.007829184 = sum of:
    0.007829184 = product of:
      0.015658367 = sum of:
        0.015658367 = weight(_text_:of in 5242) [ClassicSimilarity], result of:
          0.015658367 = score(doc=5242,freq=14.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.22855641 = fieldWeight in 5242, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5242)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

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

Source

Journal of the American Society for Information Science and Technology. 53(2002) no.9, S.716-727

0.002609728 = product of:
  0.007829184 = sum of:
    0.007829184 = product of:
      0.015658367 = sum of:
        0.015658367 = weight(_text_:of in 3623) [ClassicSimilarity], result of:
          0.015658367 = score(doc=3623,freq=14.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.22855641 = fieldWeight in 3623, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3623)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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.

Source

Journal of documentation. 66(2010) no.2, S.191-206

0.002609728 = product of:
  0.007829184 = sum of:
    0.007829184 = product of:
      0.015658367 = sum of:
        0.015658367 = weight(_text_:of in 4624) [ClassicSimilarity], result of:
          0.015658367 = score(doc=4624,freq=14.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.22855641 = fieldWeight in 4624, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4624)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Limited research has investigated the role of multitasking, cognitive coordination, and cognitive shifts during web search. Understanding these three behaviors is crucial to web search model development. This study aims to explore characteristics of multitasking behavior, types of cognitive shifts, and levels of cognitive coordination as well as the relationship between them during web search. Data collection included pre- and postquestionnaires, think-aloud protocols, web search logs, observations, and interviews with 42 graduate students who conducted 315 web search sessions with 221 information problems. Results show that web search is a dynamic interaction including the ordering of multiple information problems and the generation of evolving information problems, including task switching, multitasking, explicit task and implicit mental coordination, and cognitive shifting. Findings show that explicit task-level coordination is closely linked to multitasking, and implicit cognitive-level coordination is related to the task-coordination process; including information problem development and task switching. Coordination mechanisms directly result in cognitive state shifts including strategy, evaluation, and view states that affect users' holistic shifts in information problem understanding and knowledge contribution. A web search model integrating multitasking, cognitive coordination, and cognitive shifts (MCC model) is presented. Implications and further research also are discussed.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1446-1472

0.0024953773 = product of:
  0.007486132 = sum of:
    0.007486132 = product of:
      0.014972264 = sum of:
        0.014972264 = weight(_text_:of in 637) [ClassicSimilarity], result of:
          0.014972264 = score(doc=637,freq=20.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.21854173 = fieldWeight in 637, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03125 = fieldNorm(doc=637)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

New Directions in Cognitive Information Retrieval (IR) gathers user or cognitive approaches to IR research into one volume. The group of researchers focus on a middleground perspective between system and user. They ask the question: What is the nexus between the wider context of why and how humans behave when seeking information and the technological and other constraints that determine the interaction between user and machine? These researchers' concern for the application of user/cognitive-oriented research to IR system design thus serves as a meeting ground linking computer scientists with their largely system performance concerns and the social science research that examines human information behavior in the wider context of how human perception and cognitive mechanisms function, and the work and social frameworks in which we live. The researchers in this volume provide an in-depth revaluation of the concepts that form the basis of current IR retrieval system design. Current IR systems are in a certain sense based on design conceptualizations that view - the user's role in the user-system interaction as an input and monitoring mechanism for system performance; - the system's role in the user-system interaction as a data acquisition system, not an information retrieval system; and - the central issue in the user-system interaction as the efficacy of the system's matching algorithms, matching the user request statement to representations of the document set contained in the system's database. But the era of matching-focused approaches to interactive IR appears to be giving way to a concern for developing interactive systems to facilitate collaboration between users in the performance of their work and social tasks. There is room for cognitive approaches to interaction to break in here.

0.0024953773 = product of:
  0.007486132 = sum of:
    0.007486132 = product of:
      0.014972264 = sum of:
        0.014972264 = weight(_text_:of in 647) [ClassicSimilarity], result of:
          0.014972264 = score(doc=647,freq=20.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.21854173 = fieldWeight in 647, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03125 = fieldNorm(doc=647)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Humans have used electronic information retrieval (IR) systems for more than 50 years as they evolved from experimental systems to full-scale Web search engines and digital libraries. The fields of library and information science (LIS), cognitive science, human factors and computer science have historically been the leading disciplines in conducting research that seeks to model human interaction with IR systems for all kinds of information related behaviors. As technology problems have been mastered, the theoretical and applied framework for studying human interaction with IR systems has evolved from systems-centered to more user-centered, or cognitive-centered approaches. However, cognitive information retrieval (CIR) research that focuses on user interaction with IR systems is still largely under-funded and is often not included at computing and systems design oriented conferences. But CIR-focused research continues, and there are signs that some IR systems designers in academia and the Web search business are realizing that user behavior research can provide valuable insights into systems design and evaluation. The goal of our book is to provide an overview of new CIR research directions. This book does not provide a history of the research field of CIR. Instead, the book confronts new ways of looking at the human information condition with regard to our increasing need to interact with IR systems. The need has grown due to a number of factors, including the increased importance of information to more people in this information age. Also, IR was once considered document-oriented, but has now evolved to include multimedia, text, and other information objects. As a result, IR systems and their complexity have proliferated as users and user purposes for using them have also proliferated. Human interaction with IR systems can often be frustrating as people often lack an understanding of IR system functionality.

0.0023673228 = product of:
  0.0071019684 = sum of:
    0.0071019684 = product of:
      0.014203937 = sum of:
        0.014203937 = weight(_text_:of in 316) [ClassicSimilarity], result of:
          0.014203937 = score(doc=316,freq=2.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.20732689 = fieldWeight in 316, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.09375 = fieldNorm(doc=316)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Source

Proceedings of the 18th National Online Meeting 1997, New York, 13.-15.5.1997. Ed.: M.E. Williams

0.0023673228 = product of:
  0.0071019684 = sum of:
    0.0071019684 = product of:
      0.014203937 = sum of:
        0.014203937 = weight(_text_:of in 411) [ClassicSimilarity], result of:
          0.014203937 = score(doc=411,freq=2.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.20732689 = fieldWeight in 411, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.09375 = fieldNorm(doc=411)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

0.0023673228 = product of:
  0.0071019684 = sum of:
    0.0071019684 = product of:
      0.014203937 = sum of:
        0.014203937 = weight(_text_:of in 23) [ClassicSimilarity], result of:
          0.014203937 = score(doc=23,freq=8.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.20732689 = fieldWeight in 23, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=23)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

This article examines the public searching of the Web and provides an overview of recent research exploring what we know about how people search the Web. The article reports selected findings from studies conducted from 1997 to 2002 using large-scale Web user data provided by commercial Web companies, including Excite, Ask Jeeves, and AlltheWeb.com. We examined what topics people search for on the Web; how people search the Web using keywords in queries during search sessions; and the different types of searches conducted for multimedia, medical, e-commerce, sex, etc., information. Key findings include changes and differences in search topics over time, including a shift from entertainment to e-commerce searching by largely North American users. Findings show little change in current patterns of Web searching by many users from short queries and sessions. Alternatively, we see more complex searching behaviors by some users, including successive and multitasking searches.

4.9319223E-4 = product of:
  0.0014795767 = sum of:
    0.0014795767 = product of:
      0.0029591534 = sum of:
        0.0029591534 = weight(_text_:of in 1443) [ClassicSimilarity], result of:
          0.0029591534 = score(doc=1443,freq=2.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.043193102 = fieldWeight in 1443, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.01953125 = fieldNorm(doc=1443)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)