Artículos relacionados a A Behavioral Economics Approach to Interactive Information...

A Behavioral Economics Approach to Interactive Information Retrieval: Understanding and Supporting Boundedly Rational Users: 48 (The Information Retrieval Series, 48) - Tapa dura

Libro 38 de 42: The Information Retrieval

Liu, Jiqun

 
9783031232282: A Behavioral Economics Approach to Interactive Information Retrieval: Understanding and Supporting Boundedly Rational Users: 48 (The Information Retrieval Series, 48)
Tapa dura
ISBN 10: 3031232283 ISBN 13: 9783031232282
Editorial: Springer, 2023

Sinopsis

This 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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Jiqun Liu is an Assistant Professor of Data Science and Adjunct Assistant Professor of Psychology at the University of Oklahoma (OU). His research focuses on the intersection of human-centered data science, interactive information seeking/retrieval, and cognitive psychology, and seeks to apply the knowledge learned about people interacting with information in adaptive recommendation and de-biasing, user education and intelligent nudging. He has published extensively and advised students from diverse backgrounds on these research topics, obtained grant support from varying sources, and received best paper and poster awards at leading conferences.

De la contraportada

This 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 preliminaryresearch 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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2023
Idioma
Inglés
ISBN 10 
3031232283
ISBN 13 
9783031232282
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
228
Contacto del fabricante
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

Europaplatz 3,69115 Heidelberg, Germany
Heidelberg
69115
Alemania