Towards semantics-enabled distributed infrastructure for knowledge acquisition

Vasant Honavar, Doina Caragea

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

Abstract

We summarize progress on algorithms and software knowledge acquisition from large, distributed, autonomous, and semantically disparate information sources. Some key results include: scalable algorithms for constructing predictive models from data based on a novel decomposition of learning algorithms that interleaves queries for sufficient statistics from data with computations using the statistics; provably exact algorithms from distributed data (relative to their centralized counterparts); and statistically sound approaches to learning predictive models from partially specified data that arise in settings where the schema and the data semantics and hence the granularity of data differ across the different sources.

Original languageEnglish (US)
Title of host publicationSemantic Scientific Knowledge Integration - Papers from the AAAI Spring Symposium, Technical Report
Pages29-35
Number of pages7
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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  • Cite this

    Honavar, V., & Caragea, D. (2008). Towards semantics-enabled distributed infrastructure for knowledge acquisition. In Semantic Scientific Knowledge Integration - Papers from the AAAI Spring Symposium, Technical Report (pp. 29-35). (AAAI Spring Symposium - Technical Report; Vol. SS-08-05).