NDLI: AspNet: Aspect Extraction by Bootstrapping Generalization and Propagation Using an Aspect Network

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AspNet: Aspect Extraction by Bootstrapping Generalization and Propagation Using an Aspect Network

Content Provider	Springer Nature Link
Author	Xia, Yunqing Cambria, Erik Hussain, Amir
Copyright Year	2014
Abstract	Aspect-level opinion mining systems suffer from concept coverage problem due to the richness and ambiguity of natural language opinions. Aspects mentioned by review authors can be expressed in various forms, resulting in a potentially large number of missing or incomplete aspects. This work proposes a novel unsupervised method to extract aspects from raw reviews with a broader coverage. Previous research has shown that unsupervised methods based on dependency relations are promising for opinion target extraction (OTE). In this work, we introduce Aspect Network (AspNet), an AspNet that further improves existing OTE methods by providing a new framework for modeling aspects. AspNet represents the general indecomposable atom aspects and their dependency relations in a two-layered, directed, weighted graph, based on which the specific decomposable compound aspects in reviews can be effectively extracted. AspNet is constructed through an unsupervised learning method that starts from a small number of human-defined, domain-dependent aspects, and bootstraps generalization and propagation in a large volume of raw reviews. In summary, the major contributions of this work are twofold: Firstly, the proposed AspNet is a new framework in modeling aspects; secondly, an unsupervised method is proposed to construct AspNet in a bootstrapping manner within raw reviews to learn aspects automatically. Experimental results demonstrate that our proposed OTE method, based on AspNet, can achieve significant gains over baseline methods.
Starting Page	241
Ending Page	253
Page Count	13
File Format	PDF
ISSN	18669956
Journal	Cognitive Computation
Volume Number	7
Issue Number	2
e-ISSN	18669964
Language	English
Publisher	Springer US
Publisher Date	2014-09-19
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Aspect extraction Opinion mining Aspect Network Unsupervised learning Neurosciences Computation by Abstract Devices Artificial Intelligence (incl. Robotics) Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Cognitive Neuroscience Computer Science Applications Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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