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003			ES-MaUEC
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007			cr nn 008mamaa
008			220601s2009 sz | s |||| 0|eng d
020			_a9783031018985
024	7		_a10.1007/978-3-031-01898-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aZA4480 _b2009 EB
100	1		_aAgarwal, Nitin, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683470 _d1989-
245	1	0	_aModeling and Data Mining in Blogosphere _cby Nitin Agarwal, Huan Liu
250			_a1st edition 2009
264		1	_aCham _bSpringer International Publishing _c2009
300			_a1 recurso en línea (IX, 127 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 Mining and Knowledge Discovery _x2151-0075
505	0		_aModeling Blogosphere -- Blog Clustering and Community Discovery -- Influence and Trust -- Spam Filtering in Blogosphere -- Data Collection and Evaluation.
520			_aThis book offers a comprehensive overview of the various concepts and research issues about blogs or weblogs. It introduces techniques and approaches, tools and applications, and evaluation methodologies with examples and case studies. Blogs allow people to express their thoughts, voice their opinions, and share their experiences and ideas. Blogs also facilitate interactions among individuals creating a network with unique characteristics. Through the interactions individuals experience a sense of community. We elaborate on approaches that extract communities and cluster blogs based on information of the bloggers. Open standards and low barrier to publication in Blogosphere have transformed information consumers to producers, generating an overwhelming amount of ever-increasing knowledge about the members, their environment and symbiosis. We elaborate on approaches that sift through humongous blog data sources to identify influential and trustworthy bloggers leveraging content and network information. Spam blogs or "splogs" are an increasing concern in Blogosphere and are discussed in detail with the approaches leveraging supervised machine learning algorithms and interaction patterns. We elaborate on data collection procedures, provide resources for blog data repositories, mention various visualization and analysis tools in Blogosphere, and explain conventional and novel evaluation methodologies, to help perform research in the Blogosphere. The book is supported by additional material, including lecture slides as well as the complete set of figures used in the book, and the reader is encouraged to visit the book website for the latest information. Table of Contents: Modeling Blogosphere / Blog Clustering and Community Discovery / Influence and Trust / Spam Filtering in Blogosphere / Data Collection and Evaluation.
988			_aSynthesis Collection of Technology_2009
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9405884 _aBlogs
700	1		_aLiu, Huan, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _949086 _d1958-
776	0	8	_iPrinted edition: _z9783031007705
776	0	8	_iPrinted edition: _z9783031030260
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01898-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI