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007			cr nn 008mamaa
008			230510s2017 sz | s |||| 0|eng d
020			_a9783031019104
024	7		_a10.1007/978-3-031-01910-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2017 EB
100	1		_aLiu, Jialu _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9688454 _c(Computer scientist)
245	1	0	_aPhrase Mining from Massive Text and Its Applications _cby Jialu Liu, Jingbo Shang, Jiawei Han
250			_a1st edition 2017
264		1	_aCham _bSpringer International Publishing _c2017
300			_a1 recurso en línea (IX, 79 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		_aAcknowledgments -- Introduction -- Quality Phrase Mining with User Guidance -- Automated Quality Phrase Mining -- Phrase Mining Applications -- Bibliography -- Authors' Biographies .
520			_aA lot of digital ink has been spilled on "big data" over the past few years. Most of this surge owes its origin to the various types of unstructured data in the wild, among which the proliferation of text-heavy data is particularly overwhelming, attributed to the daily use of web documents, business reviews, news, social posts, etc., by so many people worldwide.A core challenge presents itself: How can one efficiently and effectively turn massive, unstructured text into structured representation so as to further lay the foundation for many other downstream text mining applications? In this book, we investigated one promising paradigm for representing unstructured text, that is, through automatically identifying high-quality phrases from innumerable documents. In contrast to a list of frequent n-grams without proper filtering, users are often more interested in results based on variable-length phrases with certain semantics such as scientific concepts, organizations, slogans, and so on. We propose new principles and powerful methodologies to achieve this goal, from the scenario where a user can provide meaningful guidance to a fully automated setting through distant learning. This book also introduces applications enabled by the mined phrases and points out some promising research directions.
988			_aSynthesis Collection of Technology_2017
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9164483 _aEditores de texto (Programas de ordenador)
700	1		_aShang, Jingbo _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9688455 _c(Computer scientist)
700	1		_aHan, Jiawei _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686325
776	0	8	_iPrinted edition: _z9783031007828
776	0	8	_iPrinted edition: _z9783031030383
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01910-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2023 _dz _eIG _zSI