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008			230401s2016 sz | s |||| 0|eng d
020			_a9783031023019
024	7		_a10.1007/978-3-031-02301-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aZA3075 _b2016 EB
100	1		_aYang, Grace Hui _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687964
245	1	0	_aDynamic Information Retrieval Modeling _cby Grace Hui Yang, Marc Sloan, Jun Wang
250			_a1st edition 2016
264		1	_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XVII, 126 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Information Concepts Retrieval and Services _x1947-9468
505	0		_aAcknowledgments -- Introduction -- Information Retrieval Frameworks -- Dynamic IR for a Single Query -- Dynamic IR for Sessions -- Dynamic IR for Recommender Systems -- Evaluating Dynamic IR Systems -- Conclusion -- Bibliography -- Authors' Biographies.
520			_aBig data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.
988			_aSynthesis Collection of Technology_2016
650		7	_2embne _9147823 _aRecuperación de la información
650		7	_2embne _9154628 _aProgramación dinámica
700	1		_aSloan, Marc _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687965
700	1		_aWang, Jun _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9678457
776	0	8	_iPrinted edition: _z9783031011733
776	0	8	_iPrinted edition: _z9783031034299
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02301-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b04/2023 _dz _eIG _zSI