000 | 03502nam a22004815i 4500 | ||
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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 |
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024 | 7 |
_a10.1007/978-3-031-02294-4 _2doi |
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050 | 4 | _aTK5105.5-5105.9 | |
072 | 7 |
_aUKN _2bicssc |
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_aCOM043000 _2bisacsh |
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072 | 7 |
_aUKN _2thema |
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082 | 0 | 4 |
_a004.6 _223 |
100 | 1 |
_aChuklin, Aleksandr. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _980964 |
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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. |
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300 |
_aXV, 99 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSynthesis Lectures on Information Concepts, Retrieval, and Services, _x1947-9468 |
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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 |
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650 | 1 | 4 |
_aComputer Communication Networks. _980965 |
700 | 1 |
_aMarkov, Ilya. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _980966 |
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700 | 1 |
_ade Rijke, Maarten. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _980967 |
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710 | 2 |
_aSpringerLink (Online service) _980968 |
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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 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-02294-4 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
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