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Integration of news content into web results

Author:

Fernando DiazAuthors Info & Claims

WSDM '09: Proceedings of the Second ACM International Conference on Web Search and Data Mining

Pages 182 - 191

https://doi.org/10.1145/1498759.1498825

Published: 09 February 2009 Publication History

Abstract

Aggregated search refers to the integration of content from specialized corpora or verticals into web search results. Aggregation improves search when the user has vertical intent but may not be aware of or desire vertical search. In this paper, we address the issue of integrating search results from a news vertical into web search results. News is particularly challenging because, given a query, the appropriate decision---to integrate news content or not---changes with time. Our system adapts to news intent in two ways. First, by inspecting the dynamics of the news collection and query volume, we can track development of and interest in topics. Second, by using click feedback, we can quickly recover from system errors. We define several click-based metrics which allow a system to be monitored and tuned without annotator effort.

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Cited By

Hlaoua L(2024)An overview of aggregation methods for social networks analysisKnowledge and Information Systems10.1007/s10115-024-02296-zOnline publication date: 12-Dec-2024
https://doi.org/10.1007/s10115-024-02296-z
Zhang YShao WChen XDu YXu XZheng DPei CZhang SJiang PGai K(2023)A Multi-Agent Framework for Recommendation with Heterogeneous Sources2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10191154(1-8)Online publication date: 18-Jun-2023
https://doi.org/10.1109/IJCNN54540.2023.10191154
Choi WKim S(2022)A Novel Probabilistic Graphical Model-Based Click Model for Vertical SearchJournal of the Korean Institute of Industrial Engineers10.7232/JKIIE.2022.48.2.13848:2(138-150)Online publication date: 15-Apr-2022
https://doi.org/10.7232/JKIIE.2022.48.2.138
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Index Terms

Integration of news content into web results
1. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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Published In

cover image ACM Conferences

WSDM '09: Proceedings of the Second ACM International Conference on Web Search and Data Mining

February 2009

314 pages

ISBN:9781605583907

DOI:10.1145/1498759

Editors:
Ricardo Baeza-Yates
Yahoo! Research, Spain
,
Paolo Boldi
Universita degli Studi di Milano, Italy
,
Berthier Ribeiro-Neto
Google Engineering, Brazil & CS Dept., Univ. Fed. de Minas Gerais, Brazil
,
B. Barla Cambazoglu
Yahoo! Research

Copyright © 2009 ACM.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
Yahoo! Research
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
Nokia
Google Inc.
SIGIR: ACM Special Interest Group on Information Retrieval
Microsoft: Microsoft

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 February 2009

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WSDM'09: Second ACM International Conference on Web Search and Web Data Mining

February 9 - 12, 2009

Barcelona, Spain

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Cited By

Hlaoua L(2024)An overview of aggregation methods for social networks analysisKnowledge and Information Systems10.1007/s10115-024-02296-zOnline publication date: 12-Dec-2024
https://doi.org/10.1007/s10115-024-02296-z
Zhang YShao WChen XDu YXu XZheng DPei CZhang SJiang PGai K(2023)A Multi-Agent Framework for Recommendation with Heterogeneous Sources2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10191154(1-8)Online publication date: 18-Jun-2023
https://doi.org/10.1109/IJCNN54540.2023.10191154
Choi WKim S(2022)A Novel Probabilistic Graphical Model-Based Click Model for Vertical SearchJournal of the Korean Institute of Industrial Engineers10.7232/JKIIE.2022.48.2.13848:2(138-150)Online publication date: 15-Apr-2022
https://doi.org/10.7232/JKIIE.2022.48.2.138
Karim NRizve MRahnavard NMian AShah M(2022)UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52688.2022.00945(9666-9676)Online publication date: Jun-2022
https://doi.org/10.1109/CVPR52688.2022.00945
Aliannejadi MZamani HCrestani FCroft W(2021)Context-aware Target Apps Selection and Recommendation for Enhancing Personal Mobile AssistantsACM Transactions on Information Systems10.1145/344767839:3(1-30)Online publication date: 5-May-2021
https://dl.acm.org/doi/10.1145/3447678
Guo JLan Y(2020)Query ClassificationQuery Understanding for Search Engines10.1007/978-3-030-58334-7_2(15-41)Online publication date: 2-Dec-2020
https://doi.org/10.1007/978-3-030-58334-7_2
Takanobu RZhuang THuang MFeng JTang HZheng B(2019)Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement LearningThe World Wide Web Conference10.1145/3308558.3313455(1771-1781)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313455
Jagerman RMarkov Ide Rijke MCulpepper JMoffat ABennett PLerman K(2019)When People Change their MindProceedings of the Twelfth ACM International Conference on Web Search and Data Mining10.1145/3289600.3290958(447-455)Online publication date: 30-Jan-2019
https://dl.acm.org/doi/10.1145/3289600.3290958
Achsas SNfaoui E(2019)An Analysis Study of Vertical Selection Task in Aggregated SearchProcedia Computer Science10.1016/j.procs.2019.01.021148(171-180)Online publication date: 2019
https://doi.org/10.1016/j.procs.2019.01.021
Papakonstantinou MDelis A(2019)PolyRecs: Improving Page–View Rates Using Real-Time Data AnalysisReal-Time Business Intelligence and Analytics10.1007/978-3-030-24124-7_7(95-112)Online publication date: 11-Oct-2019
https://doi.org/10.1007/978-3-030-24124-7_7
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