Search (3 results, page 1 of 1)

  • × author_ss:"Lu, K."
  1. Mu, X.; Lu, K.; Ryu, H.: Explicitly integrating MeSH thesaurus help into health information retrieval systems : an empirical user study (2014) 0.03 
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    Abstract
    When consumers search for health information, a major obstacle is their unfamiliarity with the medical terminology. Even though medical thesauri such as the Medical Subject Headings (MeSH) and related tools (e.g., the MeSH Browser) were created to help consumers find medical term definitions, the lack of direct and explicit integration of these help tools into a health retrieval system prevented them from effectively achieving their objectives. To explore this issue, we conducted an empirical study with two systems: One is a simple interface system supporting query-based searching; the other is an augmented system with two new components supporting MeSH term searching and MeSH tree browsing. A total of 45 subjects were recruited to participate in the study. The results indicated that the augmented system is more effective than the simple system in terms of improving user-perceived topic familiarity and question-answer performance, even though we did not find users spend more time on the augmented system. The two new MeSH help components played a critical role in participants' health information retrieval and were found to allow them to develop new search strategies. The findings of the study enhanced our understanding of consumers' search behaviors and shed light on the design of future health information retrieval systems.
    Date
    25. 1.2016 18:43:29
  2. Lu, K.; Joo, S.; Lee, T.; Hu, R.: Factors that influence query reformulations and search performance in health information retrieval : a multilevel modeling approach (2017) 0.01 
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    Abstract
    Query reformulations can occur multiple times in a session, and queries observed in the same session tend to be related to each other. Due to the interdependent nature of queries in a session, it has been challenging to analyze query reformulation data while controlling for possible dependencies among queries. This study proposes a multilevel modeling approach in an attempt to analyze the effects of contextual factors and system features on types of query reformulation, as well as the relationship between types of query reformulation and search performance within a single research model. The results revealed that system features and users' educational background significantly influence users' query reformulation behaviors. Also, types of query reformulation had a significant impact on search performance. The main contribution of this study lies in that it adopted the multilevel modeling method to analyze query reformulation behavior while considering the nested structure of search session data. Multilevel analysis enables us to design an extensible research model to include both session-level and action-level factors, which provides a more extended understanding of the relationships among factors that influence query reformulation behavior and search performance. The multilevel modeling used in this study has practical implications for future query reformulation studies.
  3. Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010) 0.00 
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    Date
    28. 9.2010 12:54:22

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