poster

Diversifying product search results

Authors:

Yong YuAuthors Info & Claims

SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

Pages 1093 - 1094

https://doi.org/10.1145/2009916.2010065

Published: 24 July 2011 Publication History

Get Access

Abstract

In recent years, online shopping is becoming more and more popular. Users type keyword queries on product search systems to find relevant products, accessories, and even related products. However, existing product search systems always return very similar products on the first several pages instead of taking diversity into consideration. In this paper, we propose a novel approach to address the diversity issue in the context of product search. We transform search result diversification into a combination of diversifying product categories and diversifying product attribute values within each category. The two sub-problems are optimization problems which can be reduced into well-known NP-hard problems respectively. We further leverage greedy-based approximation algorithms for efficient product search results re-ranking.

References

[1]

R. Agrawal, S. Gollapudi, A. Halverson, and S. Ieong. Diversifying Search Results. In WSDM '09. ACM, 2009.

Digital Library

Google Scholar

[2]

J. Carbonell and J. Goldstein. The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries. In SIGIR '98. ACM, 1998.

Digital Library

Google Scholar

[3]

S. Gollapudi and A. Sharma. An Axiomatic Approach for Result Diversification. In WWW '09. ACM, 2009.

Digital Library

Google Scholar

Cited By

View all

Deng ZDou ZZhu YQin XCheng PWu JWang HHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)JDivPS: A Diversified Product Search DatasetProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657888(1152-1161)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657888
Wu LGrbovic MLi JLewin-Eytan LCarmel DYom-Tov EAgichtein EGabrilovich E(2021)Toward User Engagement Optimization in 2D PresentationProceedings of the 14th ACM International Conference on Web Search and Data Mining10.1145/3437963.3441749(1047-1055)Online publication date: 8-Mar-2021
https://dl.acm.org/doi/10.1145/3437963.3441749
Karmaker Santu SSondhi PZhai CKando NSakai TJoho HLi Hde Vries AWhite R(2017)On Application of Learning to Rank for E-Commerce SearchProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080838(475-484)Online publication date: 7-Aug-2017
https://dl.acm.org/doi/10.1145/3077136.3080838
Show More Cited By

Index Terms

Diversifying product search results
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

Recommendations

Post-ranking query suggestion by diversifying search results
SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

Query suggestion refers to the process of suggesting related queries to search engine users. Most existing researches have focused on improving the relevance of suggested queries. In this paper, we introduce the concept of diversifying the content of ...
An experimental study on re-ranking web shop search results using semantic segmentation of user profiles
Abstract
Although purchasing online has become increasingly popular, finding suitable products in Web shop environments still requires significant effort from users. This study proposes a method for re-ranking products on a Web shop’s search engine to ...
Highlights
- A novel method for re-ranking products on a Web shop’s search engine.
- The novel method increases the commercial efficiency of Web shop’s search engine.
- Existing Web shop product taxonomy exploited for semantic user profiles.
- ...
Enhancing product search by best-selling prediction in e-commerce
CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

With the rapid growth of E-Commerce on the Internet, online product search service has emerged as a popular and effective paradigm for customers to find desired products and select transactions. Most product search engines today are based on adaptations ...

Comments

Information & Contributors

Information

Published In

SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

July 2011

1374 pages

ISBN:9781450307574

DOI:10.1145/2009916

General Chairs:
Wei-Ying Ma
Microsoft Research Asia, China
,
Jian-Yun Nie
University of Montreal, Canada
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Research, Spain
,
Tat-Seng Chua
National University of Singapore
,
W. Bruce Croft
University of Massachusetts, Amherst, USA

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 July 2011

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Poster

Conference

SIGIR '11

Sponsor:

SIGIR

SIGIR '11: The 34th International ACM SIGIR conference on research and development in Information Retrieval

July 24 - 28, 2011

Beijing, China

Acceptance Rates

Overall Acceptance Rate 792 of 3,983 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
508
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)2

Reflects downloads up to 03 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Deng ZDou ZZhu YQin XCheng PWu JWang HHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)JDivPS: A Diversified Product Search DatasetProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657888(1152-1161)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657888
Wu LGrbovic MLi JLewin-Eytan LCarmel DYom-Tov EAgichtein EGabrilovich E(2021)Toward User Engagement Optimization in 2D PresentationProceedings of the 14th ACM International Conference on Web Search and Data Mining10.1145/3437963.3441749(1047-1055)Online publication date: 8-Mar-2021
https://dl.acm.org/doi/10.1145/3437963.3441749
Karmaker Santu SSondhi PZhai CKando NSakai TJoho HLi Hde Vries AWhite R(2017)On Application of Learning to Rank for E-Commerce SearchProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080838(475-484)Online publication date: 7-Aug-2017
https://dl.acm.org/doi/10.1145/3077136.3080838
González Pinto JBalke W(2017)Result Set Diversification in Digital Libraries Through the Use of Paper’s ClaimsDigital Libraries: Data, Information, and Knowledge for Digital Lives10.1007/978-3-319-70232-2_19(225-236)Online publication date: 3-Nov-2017
https://doi.org/10.1007/978-3-319-70232-2_19
Jabeur LSoulier LTamine LMousset P(2016)A Product Feature-Based User-Centric Ranking Model for E-Commerce SearchExperimental IR Meets Multilinguality, Multimodality, and Interaction10.1007/978-3-319-44564-9_14(174-186)Online publication date: 23-Aug-2016
https://doi.org/10.1007/978-3-319-44564-9_14
Long BBian JDong AChang YChen XLebanon GWang HZaki M(2012)Enhancing product search by best-selling prediction in e-commerceProceedings of the 21st ACM international conference on Information and knowledge management10.1145/2396761.2398671(2479-2482)Online publication date: 29-Oct-2012
https://dl.acm.org/doi/10.1145/2396761.2398671
Xie YCheng YHonbo DZhang KAgrawal AChoudhary ACambria EZhang YXia YHoward N(2012)Crowdsourcing recommendations from social sentimentProceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining10.1145/2346676.2346685(1-8)Online publication date: 12-Aug-2012
https://dl.acm.org/doi/10.1145/2346676.2346685

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Post-ranking query suggestion by diversifying search results

An experimental study on re-ranking web shop search results using semantic segmentation of user profiles

Enhancing product search by best-selling prediction in e-commerce