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POOLSIDE: An Online Probabilistic Knowledge Base for Shopping Decision Support

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Fengfeng FanAuthors Info & Claims

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

Pages 2559 - 2562

https://doi.org/10.1145/3132847.3133168

Published: 06 November 2017 Publication History

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Abstract

We present POOLSIDE, an online PrObabilistic knOwLedge base for ShoppIng DEcision support, that provides with the on-target recommendation service based on explicit user requirement. With a natural language interface, POOLSIDE can answer question in real-time. We present how to construct the knowledge base and how to enable real-time response in POOLSIDE. Finally, we demonstrate that Poolside can give high-quality product recommendations with high efficiency.(The demo video can be accessed via the link:https://www.youtube.com/watch?v=D8ALi11CUcc)

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Bhavik Pathak. 2010. A Survey of the Comparison Shopping Agent-based Decision Support Systems. Journal of Electronic Commerce Research 11, 3 (2010), 178--192.

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Cited By

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Xu BGuo SKoh EHoffswell JRossi RDu F(2022)ARShopping: In-Store Shopping Decision Support Through Augmented Reality and Immersive Visualization2022 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS54862.2022.00033(120-124)Online publication date: Oct-2022
https://doi.org/10.1109/VIS54862.2022.00033
Zhong PLi ZChen QHou BAhmed M(2021)Numerical Markov Logic Network: A Scalable Probabilistic Framework for Hybrid Knowledge InferenceInformation10.3390/info1203012412:3(124)Online publication date: 15-Mar-2021
https://doi.org/10.3390/info12030124

Index Terms

POOLSIDE: An Online Probabilistic Knowledge Base for Shopping Decision Support
1. Information systems
  1. Information systems applications
    1. Decision support systems
  2. World Wide Web
    1. Web applications
      1. Electronic commerce
        Online shopping
2. Mathematics of computing
  1. Probability and statistics
    1. Probabilistic reasoning algorithms

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Published In

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

November 2017

2604 pages

ISBN:9781450349185

DOI:10.1145/3132847

General Chairs:
Ee-Peng Lim
Singapore Management University, Singapore
,
Marianne Winslett
University of Illinois at Urbana-Champaign, USA, and Advanced Digital Sciences Center, Singapore
,
Program Chairs:
Mark Sanderson
RMIT, Australia
,
Ada Fu
Chinese University of Hong Kong, Hong Kong
,
Jimeng Sun
Georgia Tech, USA
,
Shane Culpepper
RMIT, Australia
,
Eric Lo
Chinese University of Hong Kong, Hong Kong
,
Joyce Ho
Emory University, USA
,
Debora Donato
Mix Tech, Inc., USA
,
Rakesh Agrawal
Data Insights Laboratories, USA
,
Yu Zheng
Microsoft Research Asia, China
,
Carlos Castillo
Qatar Computing Research Institute, Qatar
,
Aixin Sun
Nanyang Technological University, Singapore
,
Vincent S. Tseng
National Cheng Kung University, Taiwan
,
Chenliang Li
Wuhan University, China

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2017

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Funding Sources

Natural Science Foundation of China
Ministry of Science and Technology of China, National Key Research and Development Program

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CIKM '17

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CIKM '17: ACM Conference on Information and Knowledge Management

November 6 - 10, 2017

Singapore, Singapore

Acceptance Rates

CIKM '17 Paper Acceptance Rate 171 of 855 submissions, 20%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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Xu BGuo SKoh EHoffswell JRossi RDu F(2022)ARShopping: In-Store Shopping Decision Support Through Augmented Reality and Immersive Visualization2022 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS54862.2022.00033(120-124)Online publication date: Oct-2022
https://doi.org/10.1109/VIS54862.2022.00033
Zhong PLi ZChen QHou BAhmed M(2021)Numerical Markov Logic Network: A Scalable Probabilistic Framework for Hybrid Knowledge InferenceInformation10.3390/info1203012412:3(124)Online publication date: 15-Mar-2021
https://doi.org/10.3390/info12030124

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Regular Expression Based Online Aided Decision Making Knowledge Base for Quality and Security of Food Processing

LINDEN: linking named entities with knowledge base via semantic knowledge

Research on Knowledge Model for Ontology-Based Knowledge Base