research-article

Unsupervised Extraction of Popular Product Attributes from E-Commerce Web Sites by Considering Customer Reviews

Authors:

Wai LamAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 16, Issue 2

Article No.: 12, Pages 1 - 17

https://doi.org/10.1145/2857054

Published: 15 April 2016 Publication History

Abstract

We develop an unsupervised learning framework for extracting popular product attributes from product description pages originated from different E-commerce Web sites. Unlike existing information extraction methods that do not consider the popularity of product attributes, our proposed framework is able to not only detect popular product features from a collection of customer reviews but also map these popular features to the related product attributes. One novelty of our framework is that it can bridge the vocabulary gap between the text in product description pages and the text in customer reviews. Technically, we develop a discriminative graphical model based on hidden Conditional Random Fields. As an unsupervised model, our framework can be easily applied to a variety of new domains and Web sites without the need of labeling training samples. Extensive experiments have been conducted to demonstrate the effectiveness and robustness of our framework.

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Cited By

Kleemann TLoepp BZiegler J(2024)Knowledge Graph-Based Integration of Conversational Advisors and Faceted FilteringInteracting with Computers10.1093/iwc/iwae044Online publication date: 18-Sep-2024
https://doi.org/10.1093/iwc/iwae044
Sarkhel RHuang BLockard CShiralkar P(2023)Self-Training for Label-Efficient Information Extraction from Semi-Structured Web-PagesProceedings of the VLDB Endowment10.14778/3611479.361151116:11(3098-3110)Online publication date: 24-Aug-2023
https://dl.acm.org/doi/10.14778/3611479.3611511
Uzun E(2023)Scraping Relevant Images from Web Pages without DownloadACM Transactions on the Web10.1145/361684918:1(1-27)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.1145/3616849
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Index Terms

Unsupervised Extraction of Popular Product Attributes from E-Commerce Web Sites by Considering Customer Reviews
1. Information systems
  1. Data management systems
    1. Information integration
      1. Extraction, transformation and loading
  2. Information retrieval
    1. Retrieval tasks and goals
      1. Information extraction

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Published In

cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 16, Issue 2

April 2016

150 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/2909066

Editor:
Munindar P. Singh
Department of Computer Science, North Carolina State University

Issue’s Table of Contents

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 April 2016

Accepted: 01 December 2015

Revised: 01 November 2015

Received: 01 November 2013

Published in TOIT Volume 16, Issue 2

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Research Grant Council of the Hong Kong Special Administrative Region, China
The Hong Kong Institute of Education
Direct Grant of the Faculty of Engineering, CUHK

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Cited By

Kleemann TLoepp BZiegler J(2024)Knowledge Graph-Based Integration of Conversational Advisors and Faceted FilteringInteracting with Computers10.1093/iwc/iwae044Online publication date: 18-Sep-2024
https://doi.org/10.1093/iwc/iwae044
Sarkhel RHuang BLockard CShiralkar P(2023)Self-Training for Label-Efficient Information Extraction from Semi-Structured Web-PagesProceedings of the VLDB Endowment10.14778/3611479.361151116:11(3098-3110)Online publication date: 24-Aug-2023
https://dl.acm.org/doi/10.14778/3611479.3611511
Uzun E(2023)Scraping Relevant Images from Web Pages without DownloadACM Transactions on the Web10.1145/361684918:1(1-27)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.1145/3616849
Budhi GChiong R(2023)A Multi-type Classifier Ensemble for Detecting Fake Reviews Through Textual-based Feature ExtractionACM Transactions on Internet Technology10.1145/356867623:1(1-24)Online publication date: 5-Apr-2023
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Xiong Y(2023)Marketing strategy of characteristic agricultural products under the background of ‘internet +’Production Planning & Control10.1080/09537287.2023.2169649(1-12)Online publication date: 6-Mar-2023
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Kleemann TZiegler J(2023)Blending Conversational Product Advisors and Faceted Filtering in a Graph-Based ApproachHuman-Computer Interaction – INTERACT 202310.1007/978-3-031-42286-7_8(137-159)Online publication date: 28-Aug-2023
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Vedula NCollins MAgichtein ERokhlenko O(2022)What Matters for Shoppers: Investigating Key Attributes for Online Product ComparisonAdvances in Information Retrieval10.1007/978-3-030-99739-7_27(231-239)Online publication date: 5-Apr-2022
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Wang JDai Y(2021)The Agglomeration Mechanism of Network Emerging E-Eommerce Industry Based on Social ScienceJournal of Organizational and End User Computing10.4018/JOEUC.29156134:3(1-16)Online publication date: 17-Nov-2021
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Liu JPan BZhang XLi D(2021)Mobile E-Commerce Information System Based on Industry Cluster under Edge ComputingMobile Information Systems10.1155/2021/79307992021Online publication date: 1-Jan-2021
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Li HWei BLiu JGuo ZQi JWu BLiu YShi Y(2021)ToFM: Topic-specific Facet Mining by Facet Propagation within Clusters2021 IEEE International Conference on Big Knowledge (ICBK)10.1109/ICKG52313.2021.00060(402-409)Online publication date: Dec-2021
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