NDLI: Mining Positive Relevance Feedback to Determine User Information Needs

Content Provider	Springer Nature Link
Author	Algarni, Abdulmohsen
Copyright Year	2014
Abstract	It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Term-based approaches are used to extract a large number of features, most of which are meaningless noise, and suffer from polysemy and synonymy. Most popular text mining techniques consider the distribution of terms in documents and data sets when calculating the weight of the terms. The innovative technique presented in this paper is called Specific Feature Discovery and is uses positive feedback only to discover positive patterns as high-level features to consider relationship among terms, then high-level patterns deployed to low-level terms to overcome the limitation of patterns. To improve the quality of the extracted features, high-level patterns are extracted from feedback documents. Following this, low-level terms extracted from high-level patterns. Determining the weight of the low-level terms is based on the distribution of the terms in the high-level patterns and the specificity of the terms in a positive group of documents. The specificity of the low-level terms is calculated according to the frequency of the terms in the documents and the frequency of the terms in extracted patterns. There have been extensive experiments in which this technique has been tested using the Reuters Corpus Volume 1 data set and Text REtrieval Conference topics. The results show that the proposed method achieves an encouraging performance in all measures.
Starting Page	8765
Ending Page	8774
Page Count	10
File Format	PDF
ISSN	13198025
Journal	Arabian Journal for Science and Engineering
Volume Number	39
Issue Number	12
e-ISSN	21914281
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-11-12
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Text mining Pattern mining Information filtering Relevance feedback Features extraction Engineering Science
Content Type	Text
Resource Type	Article

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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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