Scientific data and document processing in ChemXSeer

Prasenjit Mitra, C. Lee Giles, Bingjun Sun, Ying Liu, Anuj R. Jaiswal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

ChemXSeer is a digital library and a data repository for the chemistry domain. The data deposited into our repository is linked with digital documents to create aggregates of resources representing the links between the data and the articles in which the data is reported. ChemXSeer enables the user to annotate the data using a metadata capturing tool. The metadata is indexed and searched to return relevant datasets to the user. ChemXSeer extracts chemical formulae and chemical names, disambiguates them and indexes them to allow for domain-knowledge enhanced search capabilities. As search engines mature, we foresee such vertical search engines, employing domain-specific knowledge to perform information extraction and indexing, especially for scientific domains, become more popular. Though substantial research has been pursued on information extraction from text, extracting information from tables and figures has received little attention. In the ChemXSeer project, we are building tools that allow automatic extraction of tables and figures.

Original languageEnglish (US)
Title of host publicationSemantic Scientific Knowledge Integration - Papers from the AAAI Spring Symposium, Technical Report
Pages51-56
Number of pages6
StatePublished - Sep 30 2008
Event2008 AAAI Spring Symposium - Stanford, CA, United States
Duration: Mar 26 2008Mar 28 2008

Publication series

NameAAAI Spring Symposium - Technical Report
VolumeSS-08-05

Other

Other2008 AAAI Spring Symposium
CountryUnited States
CityStanford, CA
Period3/26/083/28/08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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