Learning link-based naïve bayes classifiers from ontology-extended distributed data

Cornelia Caragea, Doina Caragea, Vasant Honavar

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

Abstract

We address the problem of learning predictive models from multiple large, distributed, autonomous, and hence almost invariably semantically disparate, relational data sources from a user's point of view. We show under fairly general assumptions, how to exploit data sources annotated with relevant meta data in building predictive models (e.g., classifiers) from a collection of distributed relational data sources, without the need for a centralized data warehouse, while offering strong guarantees of exactness of the learned classifiers relative to their centralized relational learning counterparts. We demonstrate an application of the proposed approach in the case of learning link-based Naïve Bayes classifiers and present results of experiments on a text classification task that demonstrate the feasibility of the proposed approach.

Original languageEnglish (US)
Title of host publicationOn the Move to Meaningful Internet Systems
Subtitle of host publicationOTM 2009 - Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009, Proceedings
Pages1139-1146
Number of pages8
EditionPART 2
DOIs
StatePublished - Dec 1 2009
EventConfederated International Conferences on On the Move to Meaningful Internet Systems, OTM 2009: CoopIS 2009, DOA 2009, IS 2009 and ODBASE 2009 - Vilamoura, Portugal
Duration: Nov 1 2009Nov 6 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5871 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherConfederated International Conferences on On the Move to Meaningful Internet Systems, OTM 2009: CoopIS 2009, DOA 2009, IS 2009 and ODBASE 2009
Country/TerritoryPortugal
CityVilamoura
Period11/1/0911/6/09

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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