منابع مشابه
Context dependent semantic granularity
A fundamental issue to improve the accessibility to information resources is how to efficiently deal with huge amount(s) of data. In this respect, ontology driven techniques are expected to improve the overlap between the Cognitive Space applied by the user and the Information Space, which is defined by the information providers. In this paper we describe a powerful method to extract semantic g...
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Publication information Lovrek, I., Howlett, R. J., Jain, L. C. (eds.) Knowledge-based intelligent information and engineering systems : 12th International Conference, KES 2008, agreb, Croatia, 3-5 September 2008 : Proceedings, part II Conference details Presented at the 12th International Conference on KnowledgeBased Intelligent Information and Engineering Systems (KES 2008), Zagreb, Croatia, ...
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In this paper we describe a framework for the application of semantic granularities to the Semantic Web. Given a data source and an ontology formalizing qualities which describe the source, we define a dynamic granularity system for the navigation of the repository according to different levels of detail, i.e., granularities. Semantic granularities summarize the degree of informativeness of the...
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We present an approach for learning context-dependent semantic parsers to identify and interpret time expressions. We use a Combinatory Categorial Grammar to construct compositional meaning representations, while considering contextual cues, such as the document creation time and the tense of the governing verb, to compute the final time values. Experiments on benchmark datasets show that our a...
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Ontologies are the backbone of the emerging Semantic Web, which is envisioned to dramatically improve current web services by extending them with intelligent capabilities such as reasoning and context-awareness. They define a shared vocabulary of common domains accessible to both, humans and computers, and support various types of information management including storage and processing of data....
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ژورنال
عنوان ژورنال: International Journal of Data Mining, Modelling and Management
سال: 2011
ISSN: 1759-1163,1759-1171
DOI: 10.1504/ijdmmm.2011.041495