research-article

Acquisition of instance attributes via labeled and related instances

Authors:

Enrique Alfonseca,

Enrique Robledo-ArnuncioAuthors Info & Claims

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

Pages 58 - 65

https://doi.org/10.1145/1835449.1835462

Published: 19 July 2010 Publication History

Abstract

This paper presents a method for increasing the quality of automatically extracted instance attributes by exploiting weakly-supervised and unsupervised instance relatedness data. This data consists of (a) class labels for instances and (b) distributional similarity scores. The method organizes the text-derived data into a graph, and automatically propagates attributes among related instances, through random walks over the graph. Experiments on various graph topologies illustrate the advantage of the method over both the original attribute lists and a per-class attribute extractor, both in terms of the number of attributes extracted per instance and the accuracy of the top-ranked attributes.

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Cited By

Yang MChen KSun SHan ZKong LMeng Q(2022)A Pattern Driven Graph Ranking Approach to Attribute Extraction for Knowledge GraphIEEE Transactions on Industrial Informatics10.1109/TII.2021.307372618:2(1250-1259)Online publication date: Feb-2022
https://doi.org/10.1109/TII.2021.3073726
Zhang ZSun LHan X(2016)A joint model for Entity Set Expansion and Attribute Extraction from web search queriesProceedings of the Thirtieth AAAI Conference on Artificial Intelligence10.5555/3016100.3016336(3101-3107)Online publication date: 12-Feb-2016
https://dl.acm.org/doi/10.5555/3016100.3016336
Bing LWong TLam W(2016)Unsupervised Extraction of Popular Product Attributes from E-Commerce Web Sites by Considering Customer ReviewsACM Transactions on Internet Technology10.1145/285705416:2(1-17)Online publication date: 15-Apr-2016
https://dl.acm.org/doi/10.1145/2857054
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Index Terms

Acquisition of instance attributes via labeled and related instances
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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cover image ACM Conferences

SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval

July 2010

944 pages

ISBN:9781450301534

DOI:10.1145/1835449

General Chairs:
Fabio Crestani
University of Lugano, CH
,
Stéphane Marchand-Maillet
University of Geneva, CH
,
Program Chairs:
Hsin-Hsi Chen
National Taiwan University, TW
,
Efthimis N. Efthimiadis
University of Washington, USA
,
Jacques Savoy
University of Neuchatel, CH

Copyright © 2010 ACM.

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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2010

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SIGIR '10

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SIGIR

SIGIR '10: The 33rd International ACM SIGIR conference on research and development in Information Retrieval

July 19 - 23, 2010

Geneva, Switzerland

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SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;

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

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Cited By

Yang MChen KSun SHan ZKong LMeng Q(2022)A Pattern Driven Graph Ranking Approach to Attribute Extraction for Knowledge GraphIEEE Transactions on Industrial Informatics10.1109/TII.2021.307372618:2(1250-1259)Online publication date: Feb-2022
https://doi.org/10.1109/TII.2021.3073726
Zhang ZSun LHan X(2016)A joint model for Entity Set Expansion and Attribute Extraction from web search queriesProceedings of the Thirtieth AAAI Conference on Artificial Intelligence10.5555/3016100.3016336(3101-3107)Online publication date: 12-Feb-2016
https://dl.acm.org/doi/10.5555/3016100.3016336
Bing LWong TLam W(2016)Unsupervised Extraction of Popular Product Attributes from E-Commerce Web Sites by Considering Customer ReviewsACM Transactions on Internet Technology10.1145/285705416:2(1-17)Online publication date: 15-Apr-2016
https://dl.acm.org/doi/10.1145/2857054
Liu HDuan J(2016)An Analysis of the Relation Between Similarity Positions and Attributes of Concepts by Distance GeometryChinese Lexical Semantics10.1007/978-3-319-49508-8_38(405-415)Online publication date: 27-Nov-2016
https://doi.org/10.1007/978-3-319-49508-8_38
Blanco ROttaviano GMeij ECheng XLi HGabrilovich ETang J(2015)Fast and Space-Efficient Entity Linking for QueriesProceedings of the Eighth ACM International Conference on Web Search and Data Mining10.1145/2684822.2685317(179-188)Online publication date: 2-Feb-2015
https://dl.acm.org/doi/10.1145/2684822.2685317
Liu RZhang XWebb JLi S(2015)Context-specific intention awareness through web query in robotic caregiving2015 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA.2015.7139455(1962-1967)Online publication date: May-2015
https://doi.org/10.1109/ICRA.2015.7139455
Saha Roy RKatare RGanguly NLaxman SChoudhury M(2015)Discovering and understanding word level user intent in Web search queriesWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2014.07.01030:C(22-38)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1016/j.websem.2014.07.010
Panem SGupta MVarma VZeng YKotoulas SHuang Z(2014)Structured Information Extraction from Natural Disaster Events on TwitterProceedings of the 5th International Workshop on Web-scale Knowledge Representation Retrieval & Reasoning10.1145/2663792.2663794(1-8)Online publication date: 3-Nov-2014
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Liao LJiang JLim EHuang HFerres LRossi GAlmeida VHerder E(2014)A study of age gaps between online friendsProceedings of the 25th ACM conference on Hypertext and social media10.1145/2631775.2631800(98-106)Online publication date: 1-Sep-2014
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Kopliku APinel-Sauvagnat KBoughanem M(2014)Aggregated searchACM Computing Surveys10.1145/252381746:3(1-31)Online publication date: 1-Jan-2014
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