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Information Retrieval Evaluation in a Changing World : Lessons Learned from 20 Years of CLEF, Hardback Book

Information Retrieval Evaluation in a Changing World : Lessons Learned from 20 Years of CLEF Hardback

Edited by Nicola Ferro, Carol Peters

Part of the The Information Retrieval Series series

Hardback

Description

This volume celebrates the twentieth anniversary of CLEF - the Cross-Language Evaluation Forum for the first ten years, and the Conference and Labs of the Evaluation Forum since – and traces its evolution over these first two decades.

CLEF’s main mission is to promote research, innovation and development of information retrieval (IR) systems by anticipating trends in information management in order to stimulate advances in the field of IR system experimentation and evaluation. The book is divided into six parts. Parts I and II provide background and context, with the first part explaining what is meant by experimental evaluation and the underlying theory, and describing how this has been interpreted in CLEF and in other internationally recognized evaluation initiatives.

Part II presents research architectures and infrastructures that have been developed to manage experimental data and to provide evaluation services in CLEF and elsewhere.

Parts III, IV andV represent the core of the book, presenting some of the most significant evaluation activities in CLEF, ranging from the early multilingual text processing exercises to the later, more sophisticated experiments on multimodal collections in diverse genres and media.

In all cases, the focus is not only on describing “what has been achieved”, but above all on “what has been learnt”.

The final part examines the impact CLEF has had on the research world and discusses current and future challenges, both academic and industrial, including the relevance of IR benchmarking in industrial settings. Mainly intended for researchers in academia and industry, it also offers useful insights and tips for practitioners in industry working on the evaluation and performance issues of IR tools, and graduate students specializing in information retrieval.

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