Query Classification
Query classification, which is to assign a search query into a given target taxonomy, has been recognized as an important technique that can bring improvements in both efficiency and effectiveness of general Web search. Various classification taxonomies h
- PDF / 4,823,400 Bytes
- 228 Pages / 439.43 x 683.15 pts Page_size
- 64 Downloads / 200 Views
Yi Chang Hongbo Deng Editors
Query Understanding for Search Engines
The Information Retrieval Series Volume 46
Series Editors ChengXiang Zhai, University of Illinois, Urbana, IL, USA Maarten de Rijke, University of Amsterdam, The Netherlands and Ahold Delhaize, Zaandam, The Netherlands Editorial Board Members Nicholas J. Belkin, Rutgers University, New Brunswick, NJ, USA Charles Clarke, University of Waterloo, Waterloo, ON, Canada Diane Kelly, University of Tennessee at Knoxville, Knoxville, TN, USA Fabrizio Sebastiani, Consiglio Nazionale delle Ricerche, Pisa, Italy
Information Retrieval (IR) deals with access to and search in mostly unstructured information, in text, audio, and/or video, either from one large file or spread over separate and diverse sources, in static storage devices as well as on streaming data. It is part of both computer and information science, and uses techniques from e.g. mathematics, statistics, machine learning, database management, or computational linguistics. Information Retrieval is often at the core of networked applications, web-based data management, or large-scale data analysis. The Information Retrieval Series presents monographs, edited collections, and advanced text books on topics of interest for researchers in academia and industry alike. Its focus is on the timely publication of state-of-the-art results at the forefront of research and on theoretical foundations necessary to develop a deeper understanding of methods and approaches. This series is abstracted/indexed in Scopus.
More information about this series at http://www.springer.com/series/6128
Yi Chang • Hongbo Deng Editors
Query Understanding for Search Engines
Editors Yi Chang Jilin University Jilin, China
Hongbo Deng Alibaba Group Zhejiang, China
ISSN 1871-7500 ISSN 2730-6836 (electronic) The Information Retrieval Series ISBN 978-3-030-58333-0 ISBN 978-3-030-58334-7 (eBook) https://doi.org/10.1007/978-3-030-58334-7 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any er
Data Loading...