000 03502nam a22004815i 4500
001 978-3-031-02294-4
003 DE-He213
005 20240730163856.0
007 cr nn 008mamaa
008 220601s2015 sz | s |||| 0|eng d
020 _a9783031022944
_9978-3-031-02294-4
024 7 _a10.1007/978-3-031-02294-4
_2doi
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM043000
_2bisacsh
072 7 _aUKN
_2thema
082 0 4 _a004.6
_223
100 1 _aChuklin, Aleksandr.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980964
245 1 0 _aClick Models for Web Search
_h[electronic resource] /
_cby Aleksandr Chuklin, Ilya Markov, Maarten de Rijke.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXV, 99 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Information Concepts, Retrieval, and Services,
_x1947-9468
505 0 _aAcknowledgments -- Introduction -- Terminology -- Basic Click Models -- Parameter Estimation -- Evaluation -- Data and Tools -- Experimental Comparison -- Advanced Click Models -- Applications -- Discussion and Directions for Future Work -- Authors' Biographies -- Index .
520 _aWith the rapid growth of web search in recent years the problem of modeling its users has started to attract more and more attention of the information retrieval community. This has several motivations. By building a model of user behavior we are essentially developing a better understanding of a user, which ultimately helps us to deliver a better search experience. A model of user behavior can also be used as a predictive device for non-observed items such as document relevance, which makes it useful for improving search result ranking. Finally, in many situations experimenting with real users is just infeasible and hence user simulations based on accurate models play an essential role in understanding the implications of algorithmic changes to search engine results or presentation changes to the search engine result page. In this survey we summarize advances in modeling user click behavior on a web search engine result page. We present simple click models as well as more complex models aimed at capturing non-trivial user behavior patterns on modern search engine result pages. We discuss how these models compare to each other, what challenges they have, and what ways there are to address these challenges. We also study the problem of evaluating click models and discuss the main applications of click models.
650 0 _aComputer networks .
_931572
650 1 4 _aComputer Communication Networks.
_980965
700 1 _aMarkov, Ilya.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980966
700 1 _ade Rijke, Maarten.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980967
710 2 _aSpringerLink (Online service)
_980968
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031011665
776 0 8 _iPrinted edition:
_z9783031034220
830 0 _aSynthesis Lectures on Information Concepts, Retrieval, and Services,
_x1947-9468
_980969
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02294-4
912 _aZDB-2-SXSC
942 _cEBK
999 _c85077
_d85077