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008 210123 ||| eng
020 |a 9781306415439 
020 |a 9780124072022 
020 |a 012407202X 
050 4 |a QA76.9.T48 
100 1 |a Long, Bo  |e editor 
245 0 0 |a Relevance ranking for vertical search engines  |c edited by Bo Long, Yi Chang 
260 |a Amsterdam  |b Elsevier/Morgan Kaufmann  |c 2014 
300 |a xxiii, 239 pages  |b illustrations (some color) 
505 0 |a News search ranking -- Medical domain search ranking -- Visual search ranking -- Mobile search ranking -- Entity ranking -- Multi-aspect relevance ranking -- Aggregated vertical search -- Cross vertical search ranking 
505 0 |a Includes bibliographical references (pages 201-221) and index 
653 |a Bases de données / Interrogation 
653 |a Moteurs de recherche / Programmation 
653 |a LANGUAGE ARTS & DISCIPLINES / Library & Information Science / General / bisacsh 
653 |a Sorting (Electronic computers) / fast 
653 |a Word Processing 
653 |a Text processing (Computer science) / fast 
653 |a Relevance / fast 
653 |a Search engines / Programming / fast 
653 |a Pertinence 
653 |a online searching / aat 
653 |a Tri (Informatique) 
653 |a Database searching / fast 
653 |a Database searching / http://id.loc.gov/authorities/subjects/sh86007858 
653 |a Text processing (Computer science) / http://id.loc.gov/authorities/subjects/sh85134304 
653 |a Relevance / http://id.loc.gov/authorities/subjects/sh85112508 
653 |a Sorting (Electronic computers) / http://id.loc.gov/authorities/subjects/sh85125332 
653 |a Traitement de texte 
653 |a Search engines / Programming / http://id.loc.gov/authorities/subjects/sh00001051 
700 1 |a Chang, Yi  |e editor 
041 0 7 |a eng  |2 ISO 639-2 
989 |b OREILLY  |a O'Reilly 
776 |z 1306415438 
776 |z 9780124072022 
776 |z 0124071716 
776 |z 012407202X 
776 |z 9781306415439 
776 |z 9780124071711 
856 4 0 |u https://learning.oreilly.com/library/view/~/9780124071711/?ar  |x Verlag  |3 Volltext 
082 0 |a 025.04 
082 0 |a 500 
520 |a In plain, uncomplicated language, and using detailed examples to explain the key concepts, models, and algorithms in vertical search ranking, Relevance Ranking for Vertical Search Engines teaches readers how to manipulate ranking algorithms to achieve better results in real-world applications. This reference book for professionals covers concepts and theories from the fundamental to the advanced, such as relevance, query intention, location-based relevance ranking, and cross-property ranking. It covers the most recent developments in vertical search ranking applications, such as freshness-based relevance theory for new search applications, location-based relevance theory for local search applications, and cross-property ranking theory for applications involving multiple verticals. Introduces ranking algorithms and teaches readers how to manipulate ranking algorithms for the best resultsCovers concepts and theories from the fundamental to the advancedDiscusses the state of the art: development of theories and practices in vertical search ranking applicationsIncludes detailed examples, case studies and real-world examples