Search (144 results, page 1 of 8)

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  1. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.08 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
    Theme
    Data Mining
  2. Castillo, C.; Baeza-Yates, R.: Web retrieval and mining (2009) 0.05 
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    Abstract
    The advent of the Web in the mid-1990s followed by its fast adoption in a relatively short time, posed significant challenges to classical information retrieval methods developed in the 1970s and the 1980s. The major challenges include that the Web is massive, dynamic, and distributed. The two main types of tasks that are carried on the Web are searching and mining. Searching is locating information given an information need, and mining is extracting information and/or knowledge from a corpus. The metrics for success when carrying these tasks on the Web include precision, recall (completeness), freshness, and efficiency.
  3. Hölzig, C.: Google spürt Grippewellen auf : Die neue Anwendung ist bisher auf die USA beschränkt (2008) 0.05 
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    Date
    3. 5.1997 8:44:22
    Theme
    Data Mining
  4. Shi, X.; Yang, C.C.: Mining related queries from Web search engine query logs using an improved association rule mining model (2007) 0.04 
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    Footnote
    Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"
    Theme
    Data Mining
  5. Search tools (1997) 0.04 
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    Abstract
    Offers brief accounts of Internet search tools. Covers the Lycos revamp; the new navigation service produced jointly by Excite and Netscape, delivering a language specific, locally relevant Web guide for Japan, Germany, France, the UK and Australia; InfoWatcher, a combination offline browser, search engine and push product from Carvelle Inc., USA; Alexa by Alexa Internet and WBI from IBM which are free and provide users with information on how others have used the Web sites which they are visiting; and Concept Explorer from Knowledge Discovery Systems, Inc., California which performs data mining from the Web, Usenet groups, MEDLINE and the US Patent and Trademark Office patent abstracts
    Theme
    Data Mining
  6. Wang, P.; Berry, M.W.; Yang, Y.: Mining longitudinal Web queries : trends and patterns (2003) 0.04 
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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.
  7. Baeza-Yates, R.; Hurtado, C.; Mendoza, M.: Improving search engines by query clustering (2007) 0.04 
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    Footnote
    Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"
    Theme
    Data Mining
  8. Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents 0.04 
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    Content
    Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
  9. Kang, X.; Wu, Y.; Ren, W.: Toward action comprehension for searching : mining actionable intents in query entities (2020) 0.04 
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    Abstract
    Understanding search engine users' intents has been a popular study in information retrieval, which directly affects the quality of retrieved information. One of the fundamental problems in this field is to find a connection between the entity in a query and the potential intents of the users, the latter of which would further reveal important information for facilitating the users' future actions. In this article, we present a novel research method for mining the actionable intents for search users, by generating a ranked list of the potentially most informative actions based on a massive pool of action samples. We compare different search strategies and their combinations for retrieving the action pool and develop three criteria for measuring the informativeness of the selected action samples, that is, the significance of an action sample within the pool, the representativeness of an action sample for the other candidate samples, and the diverseness of an action sample with respect to the selected actions. Our experiment, based on the Action Mining (AM) query entity data set from the Actionable Knowledge Graph (AKG) task at NTCIR-13, suggests that the proposed approach is effective in generating an informative and early-satisfying ranking of potential actions for search users.
  10. Whittle, M.; Eaglestone, B.; Ford, N.; Gillet, V.J.; Madden, A.: Data mining of search engine logs (2007) 0.04 
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    Theme
    Data Mining
  11. Pulido, J.R.V.: Recupracion de la information en Internet : motores y otros agentes des busqueda (1997) 0.04 
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    Footnote
    Übers. des Titels: Perspectives on the retrieval and exploitation of electronic information: data mining
  12. Liu, Y.; Zhang, M.; Cen, R.; Ru, L.; Ma, S.: Data cleansing for Web information retrieval using query independent features (2007) 0.03 
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    Footnote
    Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"
    Theme
    Data Mining
  13. Sleem-Amer, M.; Bigorgne, I.; Brizard, S.; Santos, L.D.P.D.; Bouhairi, Y. El; Goujon, B.; Lorin, S.; Martineau, C.; Rigouste, L.; Varga, L.: Intelligent semantic search engines for opinion and sentiment mining (2012) 0.03 
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    Abstract
    Over the last years, research and industry players have become increasingly interested in analyzing opinions and sentiments expressed on the social media web for product marketing and business intelligence. In order to adapt to this need search engines not only have to be able to retrieve lists of documents but to directly access, analyze, and interpret topics and opinions. This article covers an intermediate phase of the ongoing industrial research project 'DoXa' aiming at developing a semantic opinion and sentiment mining search engine for the French language. The DoXa search engine enables topic related opinion and sentiment extraction beyond positive and negative polarity using rich linguistic resources. Centering the work on two distinct business use cases, the authors analyze both unstructured Web 2.0 contents (e.g., blogs and forums) and structured questionnaire data sets. The focus is on discovering hidden patterns in the data. To this end, the authors present work in progress on opinion topic relation extraction and visual analytics, linguistic resource construction as well as the combination of OLAP technology with semantic search.
  14. Höfer, W.: Detektive im Web (1999) 0.03 
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    Date
    22. 8.1999 20:22:06
  15. Rensman, J.: Blick ins Getriebe (1999) 0.03 
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    Date
    22. 8.1999 21:22:59
  16. MacLeod, R.: Promoting a subject gateway : a case study from EEVL (Edinburgh Engineering Virtual Library) (2000) 0.02 
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    Date
    22. 6.2002 19:40:22
  17. Vidmar, D.J.: Darwin on the Web : the evolution of search tools (1999) 0.02 
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    Source
    Computers in libraries. 19(1999) no.5, S.22-28
  18. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.02 
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    Date
    25. 8.2005 17:42:22
  19. ap: Suchmaschinen in neuem Gewand : Metaspinner kennt 600 Millionen Seiten (1999) 0.02 
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    Date
    3. 5.1997 8:44:22
  20. Dunning, A.: Do we still need search engines? (1999) 0.02 
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    Source
    Ariadne. 1999, no.22

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