About this product

Product Identifiers

PublisherNow Publishers

ISBN-101680830449

ISBN-139781680830446

eBay Product ID (ePID)221987487

Product Key Features

Number of Pages170 Pages

LanguageEnglish

Publication NameInformation Retrieval with Verbose Queries

SubjectComputer Science, System Administration / Storage & Retrieval, Information Technology

Publication Year2015

TypeTextbook

Subject AreaComputers

AuthorManish Gupta, Michael Bendersky

SeriesFoundations and Trends in Information Retrieval Ser.

FormatTrade Paperback

Dimensions

Item Height0.4 in

Item Weight8.8 Oz

Item Length9.2 in

Item Width6.1 in

Additional Product Features

Intended AudienceScholarly & Professional

IllustratedYes

Table Of Content1: Introduction 2: Properties of Verbose Queries 3: Query Reduction to a Single Sub-Query 4: Query Reduction by Choosing Multiple Sub-Queries 5: Weighting Query Words and Query Concepts 6: Query Expansion by Including Related Concepts 7: Query Reformulation for Verbose Queries 8: Query Segmentation for Verbose Queries 9: Sources and Treatment of Verbose Queries 10: Summary and Research Directions. Acknowledgements. Appendices. References.

SynopsisThe first monograph to provide a coherent and organized survey on this topic. It puts together the various research pieces of the puzzle, provides a comprehensive and structured overview of diverse proposed methods, and lists several application scenarios where effective verbose query processing can make a significant difference., Information retrieval with verbose natural language queries has been generating a lot of interest in recent years. The focus of many novel search applications has shifted from short keyword queries to verbose queries. Examples include question answering systems and dialogue systems, voice search on mobile devices, and entity search engines like Facebook's Graph Search or Google's Knowledge Graph. However, the performance of textbook information retrieval techniques for such verbose queries is not as good as that for their shorter counterparts. Thus, effective handling of verbose queries has become a critical factor for adoption of information retrieval techniques in this new breed of search applications. Over the past decade, the information retrieval community has deeply explored the problem of transforming natural language verbose queries using operations like reduction, weighting, expansion, reformulation and segmentation into more effective structural representations. Information Retrieval with Verbose Queries is the first monograph to provide a coherent and organized survey on this topic. It puts together the various research pieces of the puzzle, provides a comprehensive and structured overview of diverse proposed methods, and lists several application scenarios where effective verbose query processing can make a significant difference. Information Retrieval with Verbose Queries is a very timely reference on this important topic. It is entirely based on previously published research and publicly available datasets and as such, it should prove useful for both practitioners and academic researchers interested in reproducing the reported results.