book

Relevance Ranking for Vertical Search Engines

by Bo Long, Yi Chang

January 2014

Intermediate to advanced

264 pages

8h 49m

English

Morgan Kaufmann

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1.1 Defining the Area 1.2 The Content and Organization of This Book 1.3 The Audience for This Book 1.4 Further Reading

2.1 The Learning-to-Rank Approach 2.2 Joint Learning Approach from Clickthroughs 2.3 News Clustering 2.4 Summary
Introduction 3.1 Search Engines for Electronic Health Records 3.2 Search Behavior Analysis 3.3 Relevance Ranking 3.4 Collaborative Search 3.5 Conclusion
Introduction 4.1 Generic Visual Search System 4.2 Text-Based Search Ranking 4.3 Query Example-Based Search Ranking 4.4 Concept-Based Search Ranking 4.5 Visual Search Reranking 4.6 Learning and Search Ranking 4.7 Conclusions and Future Challenges
Introduction 5.1 Ranking Signals 5.2 Ranking Heuristics 5.3 Summary and Future Directions
6.1 An Overview of Entity Ranking 6.2 Background Knowledge 6.3 Feature Space Analysis 6.4 Machine-Learned Ranking for Entities 6.5 Experiments 6.6 Conclusions
Introduction 7.1 Related Work 7.2 Problem Formulation 7.3 Learning Aggregation Functions 7.4 Experiments 7.5 Conclusions and Future Work
Introduction 8.1 Sources of Evidence 8.2 Combination of Evidence 8.3 Evaluation 8.4 Special Topics 8.5 Conclusion
Introduction 9.1 The PCDF Model 9.2 Algorithm Derivation 9.3 Experimental Evaluation 9.4 Related Work 9.5 Conclusions

Content preview from Relevance Ranking for Vertical Search Engines

Introduction

Abstract

This book aims to a present systematic study of practices and theories for vertical search ranking. The studies in this book can be categorized into two major classes. One class is single-domain-related ranking that focuses on ranking for a specific vertical, such as news search ranking, medical domain search ranking, visual search ranking, mobile search ranking, and entity search ranking. Another class is multidomain-related ranking, which focuses on ranking that involves multiple verticals, such as multiaspect ranking, aggregating vertical search ranking, and cross-vertical ranking. This chapter discusses organization, audience, and further reading for this book.

Keywords

Vertical search ranking

news search ranking ...