kLogNLP: Graph Kernel–based Relational Learning of Natural LanguageShow others and affiliations
2014 (English)In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations / [ed] K. Bontcheva; Z. Jingbo, Association for Computational Linguistics, 2014, p. 85-90Conference paper, Published paper (Refereed)
Abstract [en]
kLog is a framework for kernel-basedlearning that has already proven success-ful in solving a number of relational tasksin natural language processing. In this pa-per, we presentkLogNLP, a natural lan-guage processing module for kLog. Thismodule enriches kLog with NLP-specificpreprocessors, enabling the use of exist-ing libraries and toolkits within an elegantand powerful declarative machine learn-ing framework. The resulting relationalmodel of the domain can be extended byspecifying additional relational features ina declarative way using a logic program-ming language. This declarative approachoffers a flexible way of experimentationand a way to insert domain knowledge.
Place, publisher, year, edition, pages
Association for Computational Linguistics, 2014. p. 85-90
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:oru:diva-92168DOI: 10.3115/v1/P14-5015ISI: 000538328300015ISBN: 9781941643006 (print)OAI: oai:DiVA.org:oru-92168DiVA, id: diva2:1561276
Conference
52nd Annual Meeting of the Association-for-Computational-Linguistics (ACL), Baltimore, Maryland, USA, June 22-27, 2014
Note
Funding Agencies:
FWO G.0478. 10
European Research Council (ERC) European Commission StG 240186
2021-06-072021-06-072021-06-07Bibliographically approved