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Keyword spotting techniques for sanskrit documents

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

With advances in the field of digitization of printed documents and several mass digitization projects underway, information retrieval and document search have emerged as key research areas. However, most of the current work in these areas is limited to English and a few oriental languages. The lack of efficient solutions for Indic scripts and languages such as Sanskrit has hampered information extraction from a large body of documents of cultural and historical importance. This chapter presents two relevant topics in this area. First, we describe the use of a script specific Keyword Spotting for Sanskrit documents that makes use of domain knowledge of the script. Second, we address the needs of a digital library to provide access to a collection of documents from multiple scripts. This requires intelligent solutions which scale across different scripts. We present a script independent Keyword Spotting approach for this purpose. Experimental results illustrate the efficacy of our methods.

Original languageEnglish
Title of host publicationSanskrit Computational Linguistics - First and Second International Symposia, Revised Selected and Invited Papers
Pages403-416
Number of pages14
DOIs
StatePublished - 2009
Event1st and 2nd International Symposia on Sanskrit Computational Linguistics - Providence, RI, United States
Duration: May 15 2008May 17 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5402
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st and 2nd International Symposia on Sanskrit Computational Linguistics
Country/TerritoryUnited States
CityProvidence, RI
Period05/15/0805/17/08

Keywords

  • Document analysis
  • Document retrieval
  • Indic scripts
  • Keyword spotting
  • Optical character recognition

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