research-article

Automatic organization of human task goals for web-scale problem solving knowledge

Authors:

Sung-Hyon MyaengAuthors Info & Claims

K-CAP '13: Proceedings of the seventh international conference on Knowledge capture

Pages 81 - 88

https://doi.org/10.1145/2479832.2479846

Published: 23 June 2013 Publication History

Abstract

Problem solving knowledge is omnipresent and scattered on the Web. While extracting and gathering such knowledge has been a focus of attention, it is equally important to devise a way to organize such knowledge for both human and machine consumption with respect to task goals. As a way to provide an extensive knowledge structure for human task goals, with which human problem solving knowledge extracted from Web resources can be organized, we devised a method for automatically grouping and organizing the goal statements in a Web 2.0 site that contains over two millions how-to instruction articles covering almost all task domains. In the proposed method, task goals having semantically and task-categorically similar action types and object types are grouped together by analyzing predicate-argument association patterns across all the goal statements through bipartite EM-like modeling. The result obtained with the unsupervised machine learning algorithm was evaluated by means of a human-annotated data set in a sample domain.

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Cited By

Halioui AValtchev PDiallo A(2018)Bioinformatic Workflow Extraction from Scientific Texts based on Word Sense DisambiguationIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2018.284733615:6(1979-1990)Online publication date: 1-Nov-2018
https://doi.org/10.1109/TCBB.2018.2847336

Index Terms

Automatic organization of human task goals for web-scale problem solving knowledge
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

K-CAP '13: Proceedings of the seventh international conference on Knowledge capture

June 2013

160 pages

ISBN:9781450321020

DOI:10.1145/2479832

General Chair:
Richard Benjamins
Telefonica Digital
,
Program Chairs:
Mathieu d'Aquin
KMi, The Open University
,
Andrew Gordon
University of Southern California

Copyright © 2013 ACM.

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SIGAI: ACM Special Interest Group on Artificial Intelligence

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 June 2013

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K-CAP 2013

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SIGAI

K-CAP 2013: Knowledge Capture Conference

June 23 - 26, 2013

Banff, Canada

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K-CAP '13 Paper Acceptance Rate 13 of 60 submissions, 22%;

Overall Acceptance Rate 55 of 198 submissions, 28%

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Cited By

Halioui AValtchev PDiallo A(2018)Bioinformatic Workflow Extraction from Scientific Texts based on Word Sense DisambiguationIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2018.284733615:6(1979-1990)Online publication date: 1-Nov-2018
https://doi.org/10.1109/TCBB.2018.2847336

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