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A dynamic ontology for a dynamic reference work
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International Conference on Digital Libraries archive
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries table of contents
Vancouver, BC, Canada
SESSION: Architecture and ontologies table of contents
Pages: 288 - 297  
Year of Publication: 2007
ISBN:978-1-59593-644-8
Authors
Mathias Niepert  Indiana University, Bloomington, IN
Cameron Buckner  Indiana University, Bloomington, IN
Colin Allen  Indiana University, Bloomington, IN
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
Publisher
ACM  New York, NY, USA
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ABSTRACT

The successful deployment of digital technologies by humanities scholars presents computer scientists with a number of unique scientific and technological challenges. The task seems particularly daunting because issues in the humanities are presented in abstract language demanding the kind of subtle interpretation often thought to be beyond the scope of artificial intelligence, and humanities scholars themselves often disagree about the structure of their disciplines. The future of humanities computing depends on having tools for automatically discovering complex semantic relationships among different parts of a corpus. Digital library tools for the humanities will need to be capable of dynamically tracking the introduction of new ideas and interpretations and applying them to older texts in ways that support the needs of scholars and students.

This paper describes the design of new algorithms and the adjustment of existing algorithms to support the automated and semi-automated management of domain-rich metadata for an established digital humanities project, the Stanford Encyclopedia of Philosophy. Our approach starts with a "hand-built" formal ontology that is modified and extended by a combination of automated and semi-automated methods, thus becoming a "dynamic ontology". We assess the suitability of current information retrieval and information extraction methods for the task of automatically maintaining the ontology. We describe a novel measure of term-relatedness that appears to be particularly helpful for predicting hierarchical relationships in the ontology. We believe that our project makes a further contribution to information science by being the first to harness the collaboration inherent in a expert-maintained dynamic reference work to the task of maintaining and verifying a formal ontology. We place special emphasis on the task of bringing domain expertise to bear on all phases of the development and deployment of the system, from the initial design of the software and ontology to its dynamic use in a fully operational digital reference work.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Mathias Niepert: colleagues
Cameron Buckner: colleagues
Colin Allen: colleagues