Camtology: intelligent information access for science

Authors:
Ted Briscoe;Karl Harrison;Andrew Naish-Guzman;Andy Parker;Advaith Siddharthan;David Sinclair;Mark Slater;Rebecca Watson
Affiliations:
University of Cambridge and iLexIR Ltd.;University of Birmingham;Camtology Ltd.;University of Cambridge;University of Aberdeen;Camtology Ltd.;University of Birmingham;iLexIR Ltd.
Venue:
HLT-DEMO '10 Proceedings of the NAACL HLT 2010 Demonstration Session
Year:
2010

Citing 5
Cited 0

Fast multiresolution image querying

SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Similarity Search in High Dimensions via Hashing

VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
An annotation scheme for discourse-level argumentation in research articles

EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
The second release of the RASP system

COLING-ACL '06 Proceedings of the COLING/ACL on Interactive presentation sessions
Statistical anaphora resolution in biomedical texts

COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe a novel semantic search engine for scientific literature. The Camtology system allows for sentence-level searches of PDF files and combines text and image searches, thus facilitating the retrieval of information present in tables and figures. It allows the user to generate complex queries for search terms that are related through particular grammatical/semantic relations in an intuitive manner. The system uses Grid processing to parallelise the analysis of large numbers of papers.