Reaction RuleML
Paschke, A.;Kozlenkov, A.;Boley, H.;Kifer, M.;Tabet, S.;Dean, M.;Barrett, K · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 2014
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About 204 papers for “RuleML”
Paschke, A.;Kozlenkov, A.;Boley, H.;Kifer, M.;Tabet, S.;Dean, M.;Barrett, K · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 2014
Cited by 0Open access
Harold Boley, Mike Dean, Benjamin N. Grosof et al. · 2005
Cited by 1
Boley, Harold, Wagner, G., Tabot, S. · NPARC · 2003
NRC publication: Yes
Cited by 0
Nick Bassiliades, Antonis Bikakis, Stefania Costantini et al. · UCL Discovery (University College London) · 2017
Cited by 0
GOVERNATORI, GUIDO, ROTOLO, ANTONINO · Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · 2004
Cited by 1
Guido Governatori · 2005
This paper presents an approach for the specification and implementation of translating contracts from a human-oriented form into an executable representation for monitoring. This will be done in the setting of RuleML. The task of monitoring contract execution and performance requires a logical account of deontic and defeasible aspects of legal language; currently such aspects are not covered by RuleML; accordingly we show how to extend it to cover such notions. From its logical form, the contract will be thus transformed into a machine readable rule notation and eventually implemented as executable semantics via any mark-up languages depending on the client's preference, for contract monitoring purposes.
Cited by 6
Paul Foder, Guido Governatori, José Júlio Alfers et al. · AI Magazine · 2017
This article reports on the 10th International Web Rule Symposium, which was held at Stony Brook University in Stony Brook, New York, from July 6–9, 2016.
Cited by 0Open access
Harold Boley · Lecture notes in computer science · 2009
Cited by 8
Marcel Ball, Harold Boley, David Hirtle et al. · NPARC · 2005
This paper presents the open source reference implementation of RuleML based on modular XML Schema definitions and bidirectional OO jDREW interpreters written in Java. For the family of RuleML sublanguages, schema modularization and RDF rules are discussed. The central bidirectional interpreters are introduced via jDREW principles, and explained w.r.t. OO jDREW slots, types, OIDs, and extensions.
Cited by 9Open access
Harold Boley · Lecture notes in computer science · 2006
Cited by 51
Council Canada, Marcel Ball, Harold Boley et al. · 2005
Cited by 0
Marcel Ball, Harold Boley, David Hirtle et al. · Lecture notes in computer science · 2005
Cited by 29
Gen Zou, Harold Boley · Lecture notes in computer science · 2016
Cited by 1
Carlos Viegas Damásio, Centro De Inteligência Artificial, Giorgos Stoilos · 2006
The RuleML initiative defines a normalized markup for ex-pressing and exchange rules in the Semantic Web. However, the syntax of the language is still limited and lacks features for rep-resenting rule-based languages capable of handling uncertainty. It is desirable to have a general extension of RuleML which ac-commodates major existing languages proposed in the latest two decades. The main contribution of the paper is to propose such a general extension, showing how to encode many of the existing languages in this extension. We hope this work can also provide some insights on how to cover uncertainty in the RIF framework. 1
Cited by 0
Harold Boley · Lecture notes in computer science · 2015
Cited by 11
Monica Pandey, Bramah Hazela, Vineet Singh · 2017
Recommender systems facilitates a refined search according to requirements of the user. A similar type recommendation search can be applied for the location awareness in the various mobile devices. For instance, in Ubiquitous Computing (UbiComp) there is augmentation by people and augmentation environments with computational resources which delivers information and services without any obstruction whenever and wherever required by the user. Parallel to the aim of UbiComp, this is a multi-user location awareness system which is a user-centric design and evaluation methodology. In this paper discussing the progress of such a recommendation system is perceived, that allows users to ask for the feedback about the routes from their current geographical location to the destination. The proposed system can be useful to multiple users, for instance family members, close relatives or a group of friends, to share the information give advice, tag preferences to the routes related to user location. And based on such preferences of the routes recommendations are made. Hence in the case of emergency this gives the best recommended route to the required destination according to the user.
Cited by 1
Thomas Eiter, Giovambattista Ianni, Roman Schindlauer et al. · 2009
The need for sharing knowledge on the Web—and in particular rules in a standardized format—is an important issue. RuleML [1] has been the most prominent effort in this direction so far. Nonetheless, it turns out that none of the variants available is suitable for expressing nonmonotonic logic programs as used in the answer-set programming (ASP)
Cited by 0
Open Repository and Bibliography (University of Luxembourg) · 2019
Cited by 0Open access
Boley, Harold · NPARC · 2011
Peer reviewed: No
Cited by 0Open access
Yevgen Biletskiy, Harold Boley, Girish R. Ranganathan et al. · Interactive Technology and Smart Education · 2008
Purpose The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach As proof of concept, a rule set is implemented using the rule markup language (RuleML), a member of XML‐based languages. This representation in RuleML allows the rule base to be platform‐independent, flexibly extensible and executable. Findings The RuleML source representation is easily converted to other XML‐based languages (such as RDF, OWL and XMI) as well as incorporated into, and extracted from, existing XML‐based repositories (such as IEEE LOM and CanLOM) using XSL Transformations (XSLT). Practical implications The RuleML facts and rules represented in the positional slotted language are used by the OO jDREW reasoning engine to detect and map between semantically equivalent components of course outlines as the key step in their interoperation. In particular, this will enable the precise delivery of learning objects (e.g. course outlines) from repositories to a specific learner's context. Originality/value Although the particular scenario is discussed in the present paper, the proposed approach can be applied to other tasks related to enabling semantic interoperability.
Cited by 3