The Notion Of Relevance In Information Science
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The Notion of Relevance in Information Science
Everybody knows what relevance is. It is a "ya'know" notion, concept, idea–no need to explain whatsoever. Searching for relevant information using information technology (IT) became a ubiquitous activity in contemporary information society. Relevant information means information that pertains to the matter or problem at hand—it is directly connected with effective communication. The purpose of this book is to trace the evolution and with it the history of thinking and research on relevance in information science and related fields from the human point of view. The objective is to synthesize what we have learned about relevance in several decades of investigation about the notion in information science. This book deals with how people deal with relevance—it does not cover how systems deal with relevance; it does not deal with algorithms. Spurred by advances in information retrieval (IR) and information systems of various kinds in handling of relevance, a number of basic questions are raised: But what is relevance to start with? What are some of its properties and manifestations? How do people treat relevance? What affects relevance assessments? What are the effects of inconsistent human relevance judgments on tests of relative performance of different IR algorithms or approaches? These general questions are discussed in detail.
Relevance and Irrelevance
Author: Jan Strassheim
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2018-09-24
Relevance drives our actions and channels our attention; it shapes how we make sense of the world and communicate with each other. Irrelevance spreads a twilight which blurs the line between information we do not want to access and information we cannot access. In disciplines as diverse as philosophy, sociology, the information sciences and linguistics, “relevance” has been proposed as a key concept. This book is the first to bring together the often unrelated traditions. Researchers from different fields discuss relevance and relate it to the challenges of “irrelevance”, which have so far been neglected despite their significance for our chances of making well-informed decisions and understanding others. The contributions focus on theoretical and conceptual questions, on specific factors and fields, and on practical and political implications of relevance and irrelevance as forces which are even stronger when they remain in the background.
Introduction to Information Retrieval
Author: Christopher D. Manning
language: en
Publisher: Cambridge University Press
Release Date: 2008-07-07
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.