Towards semantics-enabled distributed infrastructure for knowledge acquisition

Vasant Honavar, Doina Caragea

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


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
Number of pages7
StatePublished - 2008
Event2008 AAAI Spring Symposium - Stanford, CA, United States
Duration: Mar 26 2008Mar 28 2008

Publication series

NameAAAI Spring Symposium - Technical Report


Other2008 AAAI Spring Symposium
Country/TerritoryUnited States
CityStanford, CA

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence


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