NDLI: User-interested-keywords set discovery using rough sets for intelligent information agents

Content Provider	IEEE Xplore Digital Library
Author	Xiaomin Ying Ming Liu Wenhua Dou
Copyright Year	2001
Description	Author affiliation: Sch. of Comput., Nat. Univ. of Defense Technol., Hunan, China (Xiaomin Ying)
Abstract	With the exponential growth of the World Wide Web, it becomes difficult and time-consuming for users to find what they are interested in. This leads to a clear demand for automated methods, commonly referred to as intelligent information agents. User interest mining, which is a key technology for implementation of intelligent information agents, has attracted much more attention recently. In content-based mining, due to the sheer amount of words in the Web pages, selecting keywords that describe users' interests is critical for the performance of intelligent information agents. Because rough sets theory shows its powerful ability in attribute selection from large data set, it has been attracting much attention since it was proposed by Z. Pawlak (1982). In this paper, we present a user-interested-keywords set discovery algorithm employing rough sets. We evaluate the classification precision of the discovered keyword sets by using the KNN classifier. The remarkable character of our algorithm is that users are not required to provide negative examples of no interest. Since users are not likely to save or spend time on anything they're not interested in, our algorithm is more reasonable and practical at this aspect. We test our algorithm on some Web pages that a user has browsed. Experiments demonstrate that our algorithm can create satisfactory user-interested-keywords set.
Sponsorship	China Assoc. Sci. & Technol.(CAST)
Starting Page	61
Ending Page	66
File Size	407245
Page Count	6
File Format	PDF
ISBN	0780370104
DOI	10.1109/ICII.2001.983722
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-10-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Rough sets Web pages Machine learning World Wide Web Information filters Information filtering Internet Web sites Intelligent agent Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

User modelling and information filtering for consumer health information

An agent-based intelligent system for information gathering from World Wide Web environment

Virtual proxy servers for WWW and intelligent agents on the Internet

Agent Based Web Browser

Ranking Web Pages Using Machine Learning Approaches

Intelligent Information Retrieval Model Based on Multi-Agents

Bookmark shared system using agent systems

Efficient information retrieval on the World Wide Web using adaptable and mobile Java agents

A multi-agent system architecture for information gathering

User-interested-keywords set discovery using rough sets for intelligent information agents

Similar Documents

User modelling and information filtering for consumer health information

An agent-based intelligent system for information gathering from World Wide Web environment

Virtual proxy servers for WWW and intelligent agents on the Internet

Agent Based Web Browser

Ranking Web Pages Using Machine Learning Approaches

Intelligent Information Retrieval Model Based on Multi-Agents

Bookmark shared system using agent systems

Efficient information retrieval on the World Wide Web using adaptable and mobile Java agents

A multi-agent system architecture for information gathering

User-interested-keywords set discovery using rough sets for intelligent information agents