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  • × author_ss:"Wang, P."
  1. Hawk, W.B.; Wang, P.: Users' interaction with the World Wide Web : problems and problem solving (1999) 0.01
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    Abstract
    In this paper, we report on the second part of an empirical study designed to observe how users interact with World Wide Web resources. Applying a holistic approach, the researches examine users' cognitive, affective, and physical behaviors during user-Web interaction in order to understand better the nature of information retrieval on the Web, the needs of Web users, and the problem-solving strategies Web users employ. From analyses and the participant verbalizations collected during monitored searches, the researchers developed a taxonomy of problem solving strategies. The coding scheme was developed based on a content analysis of the integrated process data. Information from triangulation follow-up with participants via anonymously completed questionnaires, the taxonomy, and analyses of search transcripts were collected to determine 1) what problems users encountered during the interaction and how users solved these problems; and 2) which problem-solving strategies Web users considered and selected for finding factual information. The focus of the coding was on the participants' cognitive, affective, and physical behaviors in response to the components of the problems encountered, which included problems of the following types: Web interfaces, users' mental models, and the Web information sources. Searching behavior and problem-solving patterns are described and interpreted within the relevant situational context and the problems users encountered are identified and analyzed. Both the problems users faced and their problem-solving approaches endeavored evidence a strong reliance on mental models of the features available on sites, the location of those features, and other interface design concepts
  2. Wang, P.; Li, X.: Assessing the quality of information on Wikipedia : a deep-learning approach (2020) 0.01
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    Abstract
    Currently, web document repositories have been collaboratively created and edited. One of these repositories, Wikipedia, is facing an important problem: assessing the quality of Wikipedia. Existing approaches exploit techniques such as statistical models or machine leaning algorithms to assess Wikipedia article quality. However, existing models do not provide satisfactory results. Furthermore, these models fail to adopt a comprehensive feature framework. In this article, we conduct an extensive survey of previous studies and summarize a comprehensive feature framework, including text statistics, writing style, readability, article structure, network, and editing history. Selected state-of-the-art deep-learning models, including the convolutional neural network (CNN), deep neural network (DNN), long short-term memory (LSTMs) network, CNN-LSTMs, bidirectional LSTMs, and stacked LSTMs, are applied to assess the quality of Wikipedia. A detailed comparison of deep-learning models is conducted with regard to different aspects: classification performance and training performance. We include an importance analysis of different features and feature sets to determine which features or feature sets are most effective in distinguishing Wikipedia article quality. This extensive experiment validates the effectiveness of the proposed model.
    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.1, S.16-28
  3. 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.
  4. Wang, P.; Hawk, W.B.; Tenopir, C.: Users' interaction with World Wide Web resources : an exploratory study using a holistic approach (2000) 0.01
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  5. 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.
  6. 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.
  7. Wang, P.: Information behavior and seeking (2011) 0.00
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    Date
    7. 1.2013 19:28:50
  8. 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.
  9. Wang, P.; Soergel, D.: Beyond topical relevance : document selection behaviour of real users of IR systems (1993) 0.00
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    Source
    Integrating technologies - converging professions: proceedings of the 56th Annual Meeting of the American Society for Information Science, Columbus, OH, 24-28 October 1993. Ed.: S. Bonzi
  10. Tenopir, C.; Wang, P.; Zhang, Y.; Simmons, B.; Pollard, R.: Academic users' interactions with ScienceDirect in search tasks : affective and cognitive behaviors (2008) 0.00
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    Date
    28. 7.2008 14:55:54
  11. Wang, P.; Ma, Y.; Xie, H.; Wang, H.; Lu, J.; Xu, J.: "There is a gorilla holding a key on the book cover" : young children's known picture book search strategies (2022) 0.00
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    Abstract
    There is no information search system can assist young children's known picture book search needs since the information is not organized according to their cognitive abilities and needs. Therefore, this study explored young children's known picture book search strategies and extracted picture book search elements by simulating a search scenario and playing a picture book search game. The study found 29 elements children used to search for known picture books. Then, these elements are classified into three dimensions: The first dimension is the concept category of an element. The second dimension is an element's status in the story. The third dimension indicates where an element appears in a picture book. Additionally, it revealed a young children's general search strategy: Children first use auditory elements that they hear from the adults during reading. After receiving error returns, they add visual elements that they see by themselves in picture books. The findings can not only help to understand young children's known-item search and reformulation strategies during searching but also provide theoretical support for the development of a picture book information organization schema in the search system.