RuleML 2014 Special Track: Rules and Human Language Technology
Over the last decade, there has been enormous growth in open, web-based distribution of textual material from business, legal, and government communities concerning constructs such as contracts, business processes, legal cases, regulations, policies, legislation, health services, and citizen information sources. Unstructured or semi-structured textual material makes up a large portion of what is now called Big Data. In addition, there have been dramatic improvements in the effectiveness and accuracy of Natural Language Processing (NLP) and, more broadly, Human Language Technologies (HLT), accompanied by a significant expansion of the HLT community itself. In parallel, there have been substantial developments in machine-readable, knowledge-based semantic representations. For instance, a recent RuleML-OASIS collaboration led to LegalRuleML, which bridges between legal sources and formal rules.
Nevertheless, there is a substantial knowledge-acquisition bottleneck in using HLT to translate from the textual content of Big Data to machine-readable, knowledge-based semantic representations (and from formal representations back to text). Consequently, the research and industrial communities cannot make full use of the abundance of information available in Big Data to scale up such representations. By the same token, how the representations can be applied is limited. While there have been some efforts to address the bottleneck (e.g. controlled languages such as Executable English, SBVR, or ACE) and advanced parsers with semantic translation (e.g. C&C/Boxer), much more remains to be done. The Special Track is intended to focus attention on the issues, provide an outlet for current work, and be a forum for the exchange of ideas.
The Special Track is relevant to a range of communities (e.g., in Business, Law, and Government), who are concerned with translating between human language and formal rules. For example, in the BRMS community, there is growing interest in acquiring and maintaining rules extracted from textual documents such as contracts, public or internal regulations of corporations, and policy documents. Similarly, the requirements engineering community is interested in acquiring requirements from texts and generating rules to check the software behavior. The concerns of the Special Track also bear on work in decision support and process modeling communities.
Papers of interest in the Special Track will (typically) relate to the translation of texts that are descriptive (e.g., statements of facts and rules on facts) or prescriptive (e.g., statements of obligations or prohibitions in laws, regulations, or policies) to or from semantic representations.
- Natural language interfaces for rule languages, editors, engines, and use cases
- Development of language resources, e.g. terminologies, thesauri, ontologies, and corpora
- Ontologies and vocabularies for business rules
- Information retrieval and extraction from textual corpora
- Semantic annotation of textual corpora
- Multilingual aspects of processing texts
- Rule-mining techniques and applications
- Close analysis of the alignment between linguistic expressions and rule formalisms.
- Automatic Classification of documents in corpora
- Parsing of natural language expressions into machine-readable, knowledge-based semantic representations
- Generation of natural language from those representations
- Translatability of the diverse human languages to formal rules
- Controlled languages (e.g., Executable English, ACE, SBVR, CLCE, RECON) as sources, targets, or intermediaries for rule acquisition grounded in business, legal, or government textual corpora
- Logical formalisms for human language representation (e.g., Discourse Representation Structures, the feature structures of phrase structure grammars, and the defeasible deontic logic of LegalRuleML)
- Epistemological and computational properties of HLT target formalisms
- Metrics for capturing the correspondence between text and rules (e.g., notions of 'isomorphism' between legal text and rules)
- The relationship between semantic representation and interpretation.
Important Dates for RuleML (including the special tracks)
|Extended abstract submission:||April 14, 2014|
|Extended paper submission:||April 22, 2014|
|Notification:||May 20, 2014|
|Camera ready:||June 6, 2014|
|RuleML 2014 dates:||August 18-20, 2014|
Papers must be original contributions written in English and must be submitted at EasyChair for the special track as:
- Full Papers (15 pages in the proceedings)
- Short Papers (8 pages in the proceedings)
Please upload all submissions in LNCS format. To ensure high quality, submitted papers will be carefully peer-reviewed by 3 PC members based on originality, significance, technical soundness, and clarity of exposition. Accepted papers will be published in book form in the Springer Lecture Notes in Computer Science (LNCS) series with the RuleML main track proceedings.
- Johan Bos (University of Groningen, NL)
- Jack Conrad (Thomson Reuters, USA)
- Enrico Francesconi (ITTIG-CNR, Florence, Italy)
- Brigitte Grau (LIMSI, Univ Paris 11, France)
- Norbert E. Fuchs (University of Zurich, Switzerland)
- Aldo Gangemi (LIPN, Univ. Paris 13, France)
- Matthias Grabmair (University of Pittsburgh, USA)
- Tobias Kuhn (Yale University, USA)
- Yue Ma (TCS, TU-Dresden, Germany)
- Leora Morgenstern (SAIC, Arlington, Va, USA)
- Adeline Nazarenko (LIPN, Univ. Paris 13, France)
- Wim Peters (University of Sheffield, UK)
- Rolf Schwitter (Macquarie University, Australia)
- John Sowa (VivoMind Intelligence Inc., Rockville, MD. USA)
- Daniela Tiscornia (National Research Council, Italy)
- Giulia Venturi (ILC-CNR, Italy)
- Amal Zouaq (DMCS, Royal Military College of Canada, Canada)
- Paul Fodor (Stony Brook University, USA)