Search (5 results, page 1 of 1)

  • × author_ss:"Wang, P."
  • × year_i:[2000 TO 2010}
  1. Wang, P.; Hawk, W.B.; Tenopir, C.: Users' interaction with World Wide Web resources : an exploratory study using a holistic approach (2000) 0.11
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  2. Wang, P.; Berry, M.W.; Yang, Y.: Mining longitudinal Web queries : trends and patterns (2003) 0.01
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    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.
  3. Bilal, D.; Wang, P.: Children's conceptual structures of science categories and the design of Web directories (2005) 0.01
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    Abstract
    Eleven middle school children constructed hierarchical maps for two science categories selected from two Web directories, Yahooligans! and KidsClick! For each category, children constructed a pair of maps: one without links and one with links. Forty-tour maps were analyzed to identify similarities and differences. The structures of the maps were compared to the structures employed by the directories. Children were able to construct hierarchical maps and articulate the relationships among the concepts. At the global level (whole map), children's maps were not alike and did not match the structures of the Web directories. At the local levels (superordinate and subordinate), however, children shared similarities in the conceptual configurations, especially for the concrete concepts. For these concepts, substantial overlap was found between the children's structures and those employed in the directories. For the abstract concepts the configurations were diverse and did not match those in the directories. The findings of this study have impl!cations for design of systems that are more supportive of children's conceptual structures.
  4. Wolfram, D.; Wang, P.; Zhang, J.: Identifying Web search session patterns using cluster analysis : a comparison of three search environments (2009) 0.01
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    Abstract
    Session characteristics taken from large transaction logs of three Web search environments (academic Web site, public search engine, consumer health information portal) were modeled using cluster analysis to determine if coherent session groups emerged for each environment and whether the types of session groups are similar across the three environments. The analysis revealed three distinct clusters of session behaviors common to each environment: hit and run sessions on focused topics, relatively brief sessions on popular topics, and sustained sessions using obscure terms with greater query modification. The findings also revealed shifts in session characteristics over time for one of the datasets, away from hit and run sessions toward more popular search topics. A better understanding of session characteristics can help system designers to develop more responsive systems to support search features that cater to identifiable groups of searchers based on their search behaviors. For example, the system may identify struggling searchers based on session behaviors that match those identified in the current study to provide context sensitive help.
  5. Zhang, J.; Wolfram, D.; Wang, P.; Hong, Y.; Gillis, R.: Visualization of health-subject analysis based on query term co-occurrences (2008) 0.00
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    Abstract
    A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed.