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The notion of relevance in information science : : Everybody knows what relevance is. But, what is it really? /

By: Saracevic, Tefko [author.].
Material type: materialTypeLabelBookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on information concepts, retrieval, and services: # 50.Publisher: [San Rafael, California] : Morgan & Claypool, 2017.Description: 1 PDF (xx, 109 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9781598297690.Subject(s): Information retrieval | Relevance logic | relevance | information retrieval (IR) | relevance behavior | relevance effectsDDC classification: 028.7071 Online resources: Abstract with links to resource Also available in print.
Contents:
1. Introduction -- 1.1 Information technology and relevance -- 1.2 Purpose, objectives, organization -- 1.3 Synthesis: basics about relevance --
2. A bit of history -- 2.1 Information science -- 2.2 Information retrieval (IR) -- 2.3 Testing of IR systems and first concerns with relevance -- 2.4 Beginning of relevance experiments -- 2.5 Synthesis: historical developments related to relevance --
3. Understanding, manifestations, and attributes -- 3.1 Intuitive understanding -- 3.2 Relevance definitions: by any other name -- 3.3 Manifestations of relevance -- 3.3.1 Basic duality -- 3.3.2 Different manifestations of relevance -- 3.3.3 Relevance and topicality -- 3.3.4 Relevance and usefulness -- 3.3.5 Subjective and objective relevance -- 3.4 How does relevance happen? -- 3.5 Synthesis: attributes of relevance --
4. Models of relevance -- 4.1 Introduction -- 4.2 Systems view and model of relevance -- 4.2.1 Critiques -- 4.3 User's view and models of relevance -- 4.3.1 Stratified model of relevance -- 4.3.2 Integrated view and model -- 4.4 Split between system and user viewpoints -- 4.5 Synthesis: relevance models --
5. Theories of relevance -- 5.1 Introduction -- 5.2 Philosophy: relevance in the life-world -- 5.2.1 Applications in information science -- 5.3 Communication: relevance and cognition -- 5.3.1 Applications in information science -- 5.4 Still in search of a theory -- 5.4.1 What should a relevance theory encompass? -- 5.5 Synthesis: theory and relevance --
6. Experimental studies on behavior of relevance -- 6.1 Introduction -- 6.2 Relevance criteria and clues -- 6.3 Relevance dynamics -- 6.4 Relevance feedback -- 6.5 Synthesis: relevance behavior --
7. Experimental studies on effects of relevance -- 7.1 Introduction -- 7.2 Relevance judges -- 7.3 Relevance judgments -- 7.3.1 Beyond topical -- 7.3.2 Beyond binary -- 7.3.3 Beyond independence -- 7.3.4 Beyond stability -- 7.3.5 Beyond consistency -- 7.4 Eye-tracking and brain imaging experiments -- 7.4.1 Synthesis: relevance effects --
8. Effects of inconsistent relevance judgments on information retrieval test results -- 8.1 Introduction -- 8.2 Gold standard -- 8.2.1 Methods for obtaining gold standards for testing -- 8.3 But does it matter? -- 8.4 Synthesis: effect on IR evaluation --
9. Conclusions -- 9.1 Introduction -- 9.2 Globalization of relevance -- 9.3 Relevance and social media -- 9.4 Proprietary relevance -- 9.5 Informing systems design -- 9.6 Synthesis: basic questions -- 9.7 Finally -- References -- Author biography.
Abstract: Everybody knows what relevance is. It is a "y'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.
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Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references (pages 95-108).

1. Introduction -- 1.1 Information technology and relevance -- 1.2 Purpose, objectives, organization -- 1.3 Synthesis: basics about relevance --

2. A bit of history -- 2.1 Information science -- 2.2 Information retrieval (IR) -- 2.3 Testing of IR systems and first concerns with relevance -- 2.4 Beginning of relevance experiments -- 2.5 Synthesis: historical developments related to relevance --

3. Understanding, manifestations, and attributes -- 3.1 Intuitive understanding -- 3.2 Relevance definitions: by any other name -- 3.3 Manifestations of relevance -- 3.3.1 Basic duality -- 3.3.2 Different manifestations of relevance -- 3.3.3 Relevance and topicality -- 3.3.4 Relevance and usefulness -- 3.3.5 Subjective and objective relevance -- 3.4 How does relevance happen? -- 3.5 Synthesis: attributes of relevance --

4. Models of relevance -- 4.1 Introduction -- 4.2 Systems view and model of relevance -- 4.2.1 Critiques -- 4.3 User's view and models of relevance -- 4.3.1 Stratified model of relevance -- 4.3.2 Integrated view and model -- 4.4 Split between system and user viewpoints -- 4.5 Synthesis: relevance models --

5. Theories of relevance -- 5.1 Introduction -- 5.2 Philosophy: relevance in the life-world -- 5.2.1 Applications in information science -- 5.3 Communication: relevance and cognition -- 5.3.1 Applications in information science -- 5.4 Still in search of a theory -- 5.4.1 What should a relevance theory encompass? -- 5.5 Synthesis: theory and relevance --

6. Experimental studies on behavior of relevance -- 6.1 Introduction -- 6.2 Relevance criteria and clues -- 6.3 Relevance dynamics -- 6.4 Relevance feedback -- 6.5 Synthesis: relevance behavior --

7. Experimental studies on effects of relevance -- 7.1 Introduction -- 7.2 Relevance judges -- 7.3 Relevance judgments -- 7.3.1 Beyond topical -- 7.3.2 Beyond binary -- 7.3.3 Beyond independence -- 7.3.4 Beyond stability -- 7.3.5 Beyond consistency -- 7.4 Eye-tracking and brain imaging experiments -- 7.4.1 Synthesis: relevance effects --

8. Effects of inconsistent relevance judgments on information retrieval test results -- 8.1 Introduction -- 8.2 Gold standard -- 8.2.1 Methods for obtaining gold standards for testing -- 8.3 But does it matter? -- 8.4 Synthesis: effect on IR evaluation --

9. Conclusions -- 9.1 Introduction -- 9.2 Globalization of relevance -- 9.3 Relevance and social media -- 9.4 Proprietary relevance -- 9.5 Informing systems design -- 9.6 Synthesis: basic questions -- 9.7 Finally -- References -- Author biography.

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Everybody knows what relevance is. It is a "y'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.

Also available in print.

Title from PDF title page (viewed on September 18, 2016).

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