000			03026nam a22005175i 4500
001			978-1-4614-4702-3
003			DE-He213
005			20200421111155.0
007			cr nn 008mamaa
008			120816s2013 xxu| s |||| 0|eng d
020			_a9781461447023 _9978-1-4614-4702-3
024	7		_a10.1007/978-1-4614-4702-3 _2doi
050		4	_aQ334-342
050		4	_aTJ210.2-211.495
072		7	_aUYQ _2bicssc
072		7	_aTJFM1 _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
100	1		_aYoo, Kyung-Hyan. _eauthor.
245	1	0	_aPersuasive Recommender Systems _h[electronic resource] : _bConceptual Background and Implications / _cby Kyung-Hyan Yoo, Ulrike Gretzel, Markus Zanker.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aVI, 59 p. 9 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112
505	0		_aIntroduction -- Theoretical Background -- Source Factors -- Message Factors -- Receiver and Context Factors -- Discussion -- Implications for Recommender System Design -- Directions for future research.
520			_aWhether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding influential factors in advice seeking relationships, which is abundant in the context of human-human relationships, can provide an important framework for identifying potential influence factors in recommender system context. This book reviews the existing literature on the factors in advice seeking relationships in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.
650		0	_aComputer science.
650		0	_aData mining.
650		0	_aArtificial intelligence.
650	1	4	_aComputer Science.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aData Mining and Knowledge Discovery.
700	1		_aGretzel, Ulrike. _eauthor.
700	1		_aZanker, Markus. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461447016
830		0	_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-4702-3
912			_aZDB-2-ENG
942			_cEBK
999			_c53461 _d53461