Learning Probabilistic Ontologies with Distributed Parameter Learning

التفاصيل البيبلوغرافية
العنوان: Learning Probabilistic Ontologies with Distributed Parameter Learning
المؤلفون: COTA, Giuseppe, ZESE, Riccardo, BELLODI, Elena, LAMMA, Evelina, RIGUZZI, Fabrizio
المساهمون: Elena Bellodi, Alessio Bonfietti, Cota, Giuseppe, Zese, Riccardo, Bellodi, Elena, Lamma, Evelina, Riguzzi, Fabrizio
بيانات النشر: Sun SITE Central Europe
DEU
Aachen
سنة النشر: 2015
المجموعة: Università degli Studi di Ferrara: CINECA IRIS
مصطلحات موضوعية: Probabilistic Description Logics, Structure Learning,Parameter Learning, MapReduce, Message Passing Interface
الوصف: We consider the problem of learning both the structure and the parameters of Probabilistic Description Logics under DISPONTE. DISPONTE (DIstribution Semantics for Probabilistic ONTologiEs) adapts the distribution semantics for Probabilistic Logic Programming to Description Logics. The system LEAP for "LEArning Probabilistic description logics" learns both the structure and the parameters of DISPONTE knowledge bases (KBs) by exploiting the algorithms CELOE and EDGE. The former stands for "Class Expression Learning for Ontology Engineering" and it is used to generate good candidate axioms to add to the KB, while the latter learns the probabilistic parameters and evaluates the KB. EDGE for "Em over bDds for description loGics paramEter learning" is an algorithm for learning the parameters of probabilistic ontologies from data. In order to contain the computational cost, a distributed version of EDGE called EDGEMR was developed. EDGEMR exploits the MapReduce (MR) strategy by means of the Message Passing Interface. In this paper we propose the system LEAPMR. It is a re-engineered version of LEAP which is able to use distributed parallel parameter learning algorithms such as EDGEMR.
نوع الوثيقة: conference object
وصف الملف: ELETTRONICO
اللغة: English
Relation: ispartofbook:Proceedings of the Doctoral Consortium (AI*IA 2015 DC); Doctoral Consortium (DC) co-located with the 14th Conference of the Italian Association for Artificial Intelligence (AI*IA 2015); volume:1485; firstpage:7; lastpage:12; numberofpages:6; serie:CEUR WORKSHOP PROCEEDINGS; alleditors:Elena Bellodi, Alessio Bonfietti; http://hdl.handle.net/11392/2335558; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84977561779; http://ceur-ws.org/Vol-1485/paper2.pdf
الاتاحة: http://hdl.handle.net/11392/2335558
http://ceur-ws.org/Vol-1485/paper2.pdf
Rights: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.3E8053FF
قاعدة البيانات: BASE