Towards Parallel Nonmonotonic Reasoning with Billions of Facts

Ilias Tachmazidis, Grigoris Antoniou, Giorgos Flouris, Spyros Kotoulas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Citations (Scopus)

Abstract

We are witnessing an explosion of available data from the Web, government authorities, scientific databases, sensors and more. Such datasets could benefit from the introduction of rule sets encoding commonly accepted rules or facts, application - or domain-specific rules, commonsense knowledge etc. This raises the question of whether, how, and to what extent knowledge representation methods are capable of handling the vast amounts of data for these applications. In this paper, we consider nonmonotonic reasoning, which has traditionally focused on rich knowledge structures. In particular, we consider defeasible logic, and analyze how parallelization, using the MapReduce framework, can be used to reason with defeasible rules over huge data sets. Our experimental results demonstrate that defeasible reasoning with billions of data is performant, and has the potential to scale to trillions of facts.

Original languageEnglish
Title of host publication13th International Conference on the Principles of Knowledge Representation and Reasoning, KR 2012
PublisherAAAI press
Pages638-642
Number of pages5
ISBN (Print)9781577355601
Publication statusPublished - 17 May 2012
Event13th International Conference on the Principles of Knowledge Representation and Reasoning - Rome, Italy
Duration: 10 Jun 201214 Jun 2012
Conference number: 13
http://www.diag.uniroma1.it/kr12/ (Link to Conference Website)

Conference

Conference13th International Conference on the Principles of Knowledge Representation and Reasoning
Abbreviated titleKRR
Country/TerritoryItaly
CityRome
Period10/06/1214/06/12
Internet address

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