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Titlebook: Rules on the Web: From Theory to Applications; 8th International Sy Antonis Bikakis,Paul Fodor,Dumitru Roman Conference proceedings 2014 Sp

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51#
發(fā)表于 2025-3-30 10:49:29 | 只看該作者
52#
發(fā)表于 2025-3-30 14:51:25 | 只看該作者
Learning Business Rules with Association Rule Classifiersll datasets, and the fact that contradicting rules are generated. This paper shows that Association Rule Classification algorithms, such as CBA, solve both these problems, and provides a practical guide on using discovered rules in the Drools BRMS and on setting the ARC parameters. Experiments perfo
53#
發(fā)表于 2025-3-30 17:28:55 | 只看該作者
54#
發(fā)表于 2025-3-30 23:49:27 | 只看該作者
Conference proceedings 2014 Artificial Intelligence, ECAI 2014, held in Prague, Czech Republic, in August 2014..The 17 full and 6 short papers presented together with 3 keynote talks were carefully reviewed and selected from 48 submissions. The papers cover the following topics: semantic web rule languages and standards, rule
55#
發(fā)表于 2025-3-31 01:15:04 | 只看該作者
On Using Semantically-Aware Rules for Efficient Online Communicationifying the concrete publication workflow and content adaptation required. Furthermore, we evaluate our rule-based system using two different use cases, discussing the added value that the defined rules provide to this scenario and how they contribute to overcoming the identified challenges effectively.
56#
發(fā)表于 2025-3-31 07:18:38 | 只看該作者
Using Rules to Develop a Personalized and Social Location Information System for the Semantic Webhese rules, e) combines at run-time the above to match user context with up to date information, presented on Google Maps and f) matches user’s preferences with those of his/her nearby friends to present POI’s that are suitable to all of them. All data and rules are stored in the Sesame RDF triple store in order to be shared among various systems.
57#
發(fā)表于 2025-3-31 11:22:23 | 只看該作者
58#
發(fā)表于 2025-3-31 15:40:37 | 只看該作者
59#
發(fā)表于 2025-3-31 20:11:18 | 只看該作者
60#
發(fā)表于 2025-4-1 00:47:04 | 只看該作者
Semi-automated Vocabulary Building for Structured Legal Englishh is supported by automated suggestions of legal concepts computed by a semantic legal text analysis. We implement a proof-of-concept in the KR4IPLaw tool, which enables legal domain experts to represent their knowledge in Structured English. We evaluate the proposed approach on the basis of use cases in the domain of IP and patent law.
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