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008			230217s2023 sz | o |||| 0|eng d
020			_a9783031232299
024	7		_a10.1007/978-3-031-23229-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aZA3075 _b2023 EB
100	1		_aLiu, Jiqun _eautor _4http://id.loc.gov/vocabulary/relators/aut _9688047
245	1	0	_aA Behavioral Economics Approach to Interactive Information Retrieval : _bUnderstanding and Supporting Boundedly Rational Users _cby Jiqun Liu
250			_a1st ed 2023
264		1	_aCham _bSpringer International Publishing _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aThe Information Retrieval Series _x2730-6836 _v48
520			_aThis book brings together the insights from three different areas, Information Seeking and Retrieval, Cognitive Psychology, and Behavioral Economics, and shows how this new interdisciplinary approach can advance our knowledge about users interacting with diverse search systems, especially their seemingly irrational decisions and anomalies that could not be predicted by most normative models. The first part "Foundation" of this book introduces the general notions and fundamentals of this new approach, as well as the main concepts, terminology and theories. The second part "Beyond Rational Agents" describes the systematic biases and cognitive limits confirmed by behavioral experiments of varying types and explains in detail how they contradict the assumptions and predictions of formal models in information retrieval (IR). The third part "Toward A Behavioral Economics Approach" first synthesizes the findings from existing preliminary research on bounded rationality and behavioral economics modeling in information seeking, retrieval, and recommender system communities. Then, it discusses the implications, open questions and methodological challenges of applying the behavioral economics framework to different sub-areas of IR research and practices, such as modeling users and search sessions, developing unbiased learning to rank and adaptive recommendations algorithms, implementing bias-aware intelligent task support, as well as extending the conceptualization and evaluation on IR fairness, accountability, transparency and ethics (FATE) with the knowledge regarding both human biases and algorithmic biases. This book introduces a behavioral economics framework to IR scientists seeking a new perspective on both fundamental and new emerging problems of IR as well as the development and evaluation of bias-aware intelligent information systems. It is especially intended for researchers working on IR and human-information interaction who want to learn about the potential offered by behavioral economics in their own research areas.
988			_aSpringer_Computer_2023
650		7	_2embne _9147823 _aRecuperación de la información _xAspectos psicológicos
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-23229-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _eb _zSI