000			03304nam a2200397 i 4500
999			_c386957 _d386957
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003			ES-MaUEC
005			20230130114150.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			220601s2011 sz | o |||| 0|eng d
020			_a9783031018428
024	7		_a10.1007/978-3-031-01842-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aZA4235 _b2011 EB
100	1		_aGündüz-Ögüdücü, Şule _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686314
245	1	0	_aWeb Page Recommendation Models _cby Sule Gunduz-Oguducu
250			_a1st edition 2011
264		1	_aCham _bSpringer International Publishing _c2011
300			_a1 recurso en línea (VII, 77 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Data Management _x2153-5426
505	0		_aIntroduction to Web Page Recommender Systems -- Preprocessing for Web Page Recommender Models -- Pattern Extraction -- Evaluation Metrics.
520			_aOne of the application areas of data mining is the World Wide Web (WWW or Web), which serves as a huge, widely distributed, global information service for every kind of information such as news, advertisements, consumer information, financial management, education, government, e-commerce, health services, and many other information services. The Web also contains a rich and dynamic collection of hyperlink information, Web page access and usage information, providing sources for data mining. The amount of information on the Web is growing rapidly, as well as the number of Web sites and Web pages per Web site. Consequently, it has become more difficult to find relevant and useful information for Web users. Web usage mining is concerned with guiding the Web users to discover useful knowledge and supporting them for decision-making. In that context, predicting the needs of a Web user as she visits Web sites has gained importance. The requirement for predicting user needs in order to guide the user in a Web site and improve the usability of the Web site can be addressed by recommending pages to the user that are related to the interest of the user at that time. This monograph gives an overview of the research in the area of discovering and modeling the users' interest in order to recommend related Web pages. The Web page recommender systems studied in this monograph are categorized according to the data mining algorithms they use for recommendation. Table of Contents: Introduction to Web Page Recommender Systems / Preprocessing for Web Page Recommender Models / Pattern Extraction / Evaluation Metrics.
988			_aSynthesis Collection of Technology_2011
650		7	_2embne _9681247 _aPáginas Web _xEstudios de usuarios
776	0	8	_iPrinted edition: _z9783031007149
776	0	8	_iPrinted edition: _z9783031029707
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01842-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _eb _zSI