NDLI: Genetic Mining of HTML Structures for Effective Web-Document Retrieval

Content Provider	Springer Nature Link
Author	Kim, Sun Zhang, Byoung Tak
Copyright Year	2003
Abstract	Web-documents have a number of tags indicating the structure of texts. Text segments marked by HTML tags have specific meaning which can be utilized to improve the performance of document retrieval systems. In this paper, we present a machine learning approach to mine the structure of HTML documents for effective Web-document retrieval. A genetic algorithm is described that learns the importance factors of HTML tags which are used to re-rank the documents retrieved by standard weighting schemes. The proposed method has been evaluated on artificial text sets and a large-scale TREC document collection. Experimental evidence supports that the tag weights are well trained by the proposed algorithm in accordance with the importance factors for retrieval, and indicates that the proposed approach significantly improves the performance in retrieval accuracy. In particular, the use of the document-structure mining approach tends to move relevant documents to upper ranks, which is especially important in interactive Web-information retrieval environments.
Starting Page	243
Ending Page	256
Page Count	14
File Format	PDF
ISSN	0924669X
Journal	Applied Intelligence
Volume Number	18
Issue Number	3
e-ISSN	15737497
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2003-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial Intelligence (incl. Robotics) Mechanical Engineering Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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