NDLI: Rule based Text Extraction from a Bibliographic Database

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Rule based Text Extraction from a Bibliographic Database

Content Provider	DRDO Published Journals
Author	Makhija, Veena Ahuja, Swapnil
Abstract	The emergent concept of ‘ Big Data’ has shifted the paradigm from information retrieval to information extraction techniques. The information extraction techniques enables corpus analysis to draw useful interpretations and its possible applications. Selection of appropriate information extraction technique depends upon the type of data being dealt with and its possible applications. In an R&D environment, the published information is considered as an authenticated benchmark to study and analyse the growth pattern in that field of science, medicine, business. A rule based information extraction process, on the selected data extracted from a bibliographic database of published R&D papers is proposed in this paper. Aim of the study is to build up a database on relevant concepts, cleaning of retrieved data and automate the process of information retrieval in the local database. For this purpose, a concept based ‘subject profiles’ in the area of advanced semiconductors as well as the rules for text extraction from metadata retrieved from the bibliographic database was developed. This subset was used as an input to the knowledge domain to support R&D in the area of ‘advanced semiconductor materials and devices’ and provide information services on Intranet. Study found that concept based pattern matching on the datasets downloaded yielded better results as compared to the results by using the controlled vocabulary of the source database .
File Format	PDF
ISSN	09740643
e-ISSN	09764658
DOI	10.14429/djlit.38.1.12307
Alternate Webpage(s)	https://publications.drdo.gov.in/ojs/index.php/djlit/article/view/12307/6097
Journal	DESIDOC Journal of Library & Information Technology
Issue Number	1
Volume Number	38
Language	English
Publisher Date	2018-01-02
Publisher Institution	DRDO-Solid State Physics Laboratory, Delhi - 110 054 University of Southern California
Access Restriction	Open
Subject Keyword	Text Extraction Rule Based Information Extraction Knowledge Domain Semiconductors Controlled Vocabulary Metadata Extraction
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences

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