소장자료
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020 | ▼a9789811525131▼9978-981-15-2513-1▲ | ||
024 | 7 | ▼a10.1007/978-981-15-2513-1▼2doi▲ | |
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082 | 0 | 4 | ▼a006.76▼223▲ |
100 | 1 | ▼aVenugopal, K. R.▼eauthor.▼4aut▼4http://id.loc.gov/vocabulary/relators/aut▲ | |
245 | 1 | 0 | ▼aWeb Recommendations Systems▼h[electronic resource] /▼cby K. R. Venugopal, K. C. Srikantaiah, Sejal Santosh Nimbhorkar.▲ |
250 | ▼a1st ed. 2020.▲ | ||
264 | 1 | ▼aSingapore :▼bSpringer Singapore :▼bImprint: Springer,▼c2020.▲ | |
300 | ▼aXXI, 164 p. 43 illus., 4 illus. in color.▼bonline resource.▲ | ||
336 | ▼atext▼btxt▼2rdacontent▲ | ||
337 | ▼acomputer▼bc▼2rdamedia▲ | ||
338 | ▼aonline resource▼bcr▼2rdacarrier▲ | ||
347 | ▼atext file▼bPDF▼2rda▲ | ||
505 | 0 | ▼a1 Introduction -- 2 Web Data Extraction and Integration System for Search Engine Result Pages -- 3 Mining and Analysis of Web Sequential Patterns -- 4 Automatic Discovery and Ranking of Synonyms for Search Keywords in the Web -- 5 Construction of Topic Directories using Levenshtein Similarity Weight -- 6 Related Search Recommendation with User Feedback Session -- 7 Webpage Recommendations based Web Navigation Prediction. .▲ | |
520 | ▼aThis book focuses on Web recommender systems, offering an overview of approaches to develop these state-of-the-art systems. It also presents algorithmic approaches in the field of Web recommendations by extracting knowledge from Web logs, Web page content and hyperlinks. Recommender systems have been used in diverse applications, including query log mining, social networking, news recommendations and computational advertising, and with the explosive growth of Web content, Web recommendations have become a critical aspect of all search engines. The book discusses how to measure the effectiveness of recommender systems, illustrating the methods with practical case studies. It strikes a balance between fundamental concepts and state-of-the-art technologies, providing readers with valuable insights into Web recommender systems.▲ | ||
650 | 0 | ▼aComputer programming.▲ | |
650 | 0 | ▼aOptical data processing.▲ | |
650 | 0 | ▼aData structures (Computer science).▲ | |
650 | 0 | ▼aData mining.▲ | |
650 | 1 | 4 | ▼aWeb Development.▼0https://scigraph.springernature.com/ontologies/product-market-codes/I29050▲ |
650 | 2 | 4 | ▼aImage Processing and Computer Vision.▼0https://scigraph.springernature.com/ontologies/product-market-codes/I22021▲ |
650 | 2 | 4 | ▼aData Structures.▼0https://scigraph.springernature.com/ontologies/product-market-codes/I15017▲ |
650 | 2 | 4 | ▼aData Mining and Knowledge Discovery.▼0https://scigraph.springernature.com/ontologies/product-market-codes/I18030▲ |
700 | 1 | ▼aSrikantaiah, K. C.▼eauthor.▼4aut▼4http://id.loc.gov/vocabulary/relators/aut▲ | |
700 | 1 | ▼aSantosh Nimbhorkar, Sejal.▼eauthor.▼4aut▼4http://id.loc.gov/vocabulary/relators/aut▲ | |
710 | 2 | ▼aSpringerLink (Online service)▲ | |
773 | 0 | ▼tSpringer Nature eBook▲ | |
776 | 0 | 8 | ▼iPrinted edition:▼z9789811525124▲ |
776 | 0 | 8 | ▼iPrinted edition:▼z9789811525148▲ |
776 | 0 | 8 | ▼iPrinted edition:▼z9789811525155▲ |
856 | 4 | 0 | ▼uhttps://doi.org/10.1007/978-981-15-2513-1▲ |
912 | ▼aZDB-2-SCS▲ | ||
912 | ▼aZDB-2-SXCS▲ | ||
950 | ▼aComputer Science (SpringerNature-11645)▲ | ||
950 | ▼aComputer Science (R0) (SpringerNature-43710)▲ |
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Web Recommendations Systems
자료유형
국외eBook
서명/책임사항
Web Recommendations Systems [electronic resource] / by K. R. Venugopal, K. C. Srikantaiah, Sejal Santosh Nimbhorkar.
판사항
1st ed. 2020.
형태사항
XXI, 164 p. 43 illus., 4 illus. in color. online resource.
내용주기
1 Introduction -- 2 Web Data Extraction and Integration System for Search Engine Result Pages -- 3 Mining and Analysis of Web Sequential Patterns -- 4 Automatic Discovery and Ranking of Synonyms for Search Keywords in the Web -- 5 Construction of Topic Directories using Levenshtein Similarity Weight -- 6 Related Search Recommendation with User Feedback Session -- 7 Webpage Recommendations based Web Navigation Prediction. .
요약주기
This book focuses on Web recommender systems, offering an overview of approaches to develop these state-of-the-art systems. It also presents algorithmic approaches in the field of Web recommendations by extracting knowledge from Web logs, Web page content and hyperlinks. Recommender systems have been used in diverse applications, including query log mining, social networking, news recommendations and computational advertising, and with the explosive growth of Web content, Web recommendations have become a critical aspect of all search engines. The book discusses how to measure the effectiveness of recommender systems, illustrating the methods with practical case studies. It strikes a balance between fundamental concepts and state-of-the-art technologies, providing readers with valuable insights into Web recommender systems.
주제
ISBN
9789811525131
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