Search (4 results, page 1 of 1)

  • × author_ss:"Si, L."
  • × language_ss:"e"
  1. Avrahami, T.T.; Yau, L.; Si, L.; Callan, J.P.: ¬The FedLemur project : Federated search in the real world (2006) 0.05 
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    Abstract
    Federated search and distributed information retrieval systems provide a single user interface for searching multiple full-text search engines. They have been an active area of research for more than a decade, but in spite of their success as a research topic, they are still rare in operational environments. This article discusses a prototype federated search system developed for the U.S. government's FedStats Web portal, and the issues addressed in adapting research solutions to this operational environment. A series of experiments explore how well prior research results, parameter settings, and heuristics apply in the FedStats environment. The article concludes with a set of lessons learned from this technology transfer effort, including observations about search engine quality in the real world.
    Date
    22. 7.2006 16:02:07
  2. Ren, P.; Chen, Z.; Ma, J.; Zhang, Z.; Si, L.; Wang, S.: Detecting temporal patterns of user queries (2017) 0.02 
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    Abstract
    Query classification is an important part of exploring the characteristics of web queries. Existing studies are mainly based on Broder's classification scheme and classify user queries into navigational, informational, and transactional categories according to users' information needs. In this article, we present a novel classification scheme from the perspective of queries' temporal patterns. Queries' temporal patterns are inherent time series patterns of the search volumes of queries that reflect the evolution of the popularity of a query over time. By analyzing the temporal patterns of queries, search engines can more deeply understand the users' search intents and thus improve performance. Furthermore, we extract three groups of features based on the queries' search volume time series and use a support vector machine (SVM) to automatically detect the temporal patterns of user queries. Extensive experiments on the Million Query Track data sets of the Text REtrieval Conference (TREC) demonstrate the effectiveness of our approach.
  3. Si, L.: ¬The status quo and future development of cataloging and classification education in China (2005) 0.01 
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    Date
    29. 9.2008 19:01:22
  4. Si, L.: Encoding formats and consideration of requirements for mapping (2007) 0.01 
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    Date
    26.12.2011 13:22:27

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