Technical and Regulatory Perspectives on Information Retrieval and Recommender Systems
Technical and Regulatory Perspectives on Information Retrieval and Recommender Systems

Author: Markus Schedl

Publisher: Springer Nature

Published: 2025

Total Pages: 202

ISBN-13: 3031699785

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This book provides an in-depth treatment of three important topical areas related to regulatory, ethical, and technical discussions in the context of information retrieval and recommender systems (IRRSs): (1) bias, fairness, and non-discrimination, (2) transparency and explainability, and (3) privacy and security. Sometimes referred to as trustworthiness dimensions, they are analyzed by taking an interdisciplinary perspective and incorporating views from computer science, social sciences, psychology, and law and by particularly considering the related technical challenges, societal impact, ethical considerations, and regulatory approaches. After an introduction, the book first provides an overview of recent initiatives and already operational policies to regulate AI technology and discusses them in the context of IRRSs, focusing on regulations in Europe, the US, and China. Subsequent chapters present categories of biases, their relation to fairness and non-discrimination and ways to discover and mitigate harmful biases; major facets of transparency, with a focus on explainability (including common strategies to achieve it), traceability, and auditability; and privacy and security including technical approaches to mitigate privacy risks such as anonymization techniques and encryption methods. Eventually, the last chapter provides an outlook on the grand challenges in IRRSs, such as dealing with discrepancies between formal attempts, human perception, and regulatory frameworks for trustworthy IRRSs; understanding the capabilities and limitations of existing solutions in terms of fairness, transparency, and privacy; and adopting a multistakeholder perspective when developing solutions for fair, transparent, and privacy-preserving IRRSs. The book targets a mostly technical readership and aims to equip it with the necessary understanding of the ethical implications of their research and development in IRRSs as well as of recent policy initiatives and regulatory approaches. While a basic knowledge of IRRSs is assumed to fully comprehend the more technical and algorithmic parts of the book, even a lay audience in terms of technical background should benefit from the book.

Information Retrieval
Information Retrieval

Author: Stefan Buttcher

Publisher: MIT Press

Published: 2016-02-12

Total Pages: 633

ISBN-13: 0262528878

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An introduction to information retrieval, the foundation for modern search engines, that emphasizes implementation and experimentation. Information retrieval is the foundation for modern search engines. This textbook offers an introduction to the core topics underlying modern search technologies, including algorithms, data structures, indexing, retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes exercises and suggestions for student projects. Wumpus—a multiuser open-source information retrieval system developed by one of the authors and available online—provides model implementations and a basis for student work. The modular structure of the book allows instructors to use it in a variety of graduate-level courses, including courses taught from a database systems perspective, traditional information retrieval courses with a focus on IR theory, and courses covering the basics of Web retrieval. In addition to its classroom use, Information Retrieval will be a valuable reference for professionals in computer science, computer engineering, and software engineering.

Introduction to Information Retrieval
Introduction to Information Retrieval

Author: Christopher D. Manning

Publisher: Cambridge University Press

Published: 2008-07-07

Total Pages:

ISBN-13: 1139472100

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Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Information Retrieval
Information Retrieval

Author: William Hersh

Publisher: Springer Science & Business Media

Published: 2006-05-04

Total Pages: 524

ISBN-13: 0387226788

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Coupled with the growth of the World Wide Web, the topic of health information retrieval has had a tremendous impact on consumer health information. With the aid of newly added questions and discussions at the end of each chapter, this Second Edition covers theory practical applications, evaluation, and research directions of all aspects of medical information retireval systems.

Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)

Author: Ahmed El-Hashash

Publisher: Springer Nature

Published: 2023-01-14

Total Pages: 1083

ISBN-13: 9464630582

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This is an open access book. As a leading role in the global megatrend of scientific innovation, China has been creating a more and more open environment for scientific innovation, increasing the depth and breadth of academic cooperation, and building a community of innovation that benefits all. These endeavors have made new contribution to globalization and creating a community of shared future. To adapt to this changing world and China's fast development in this new area, the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) is to be held in April 15-17, 2022. This conference takes “bringing together global wisdom in scientific innovation to promote high-quality development" as the theme and focuses on research fields including information technology, education, big data, and Internet. This conference aims to expand channels of international academic exchange in science and technology, build a sharing platform of academic resources, promote scientific innovation on the global scale, improve academic cooperation between China and the outside world. It also aims to encourage exchange of information on research frontiers in different fields, connect the most advanced academic resources in China and abroad, turn research results into industrial solutions, bring together talents, technologies and capital to boost development.

Recommendation Systems in Software Engineering
Recommendation Systems in Software Engineering

Author: Martin P. Robillard

Publisher: Springer Science & Business

Published: 2014-04-30

Total Pages: 560

ISBN-13: 3642451357

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With the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendation systems have emerged that specifically address the unique challenges of navigating and interpreting software engineering data. This book collects, structures and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and evaluation. The book is divided into three parts: “Part I – Techniques” introduces basics for building recommenders in software engineering, including techniques for collecting and processing software engineering data, but also for presenting recommendations to users as part of their workflow. “Part II – Evaluation” summarizes methods and experimental designs for evaluating recommendations in software engineering. “Part III – Applications” describes needs, issues and solution concepts involved in entire recommendation systems for specific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materials for readers of this book and anyone interested in recommendation systems in software engineering, including lecture slides, data sets, source code, and an overview of people, groups, papers and tools with regard to recommendation systems in software engineering. The book is particularly well-suited for graduate students and researchers building new recommendation systems for software engineering applications or in other high-tech fields. It may also serve as the basis for graduate courses on recommendation systems, applied data mining or software engineering. Software engineering practitioners developing recommendation systems or similar applications with predictive functionality will also benefit from the broad spectrum of topics covered.