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Feature selection for text classification is a well-studied problem and the goals are improving classification effectiveness, computational efficiency, or both. In this paper, we propose a two-stage feature selection algorithm based on a kind of feature selection method and latent semantic indexing. Traditional word-matching based text categorization system uses vector space model to represent the...
Ontology-based documents classification method is introduced to solve the problem of classifier training and not considering semantic relations between words in traditional Machine Learning algorithms. However, previous work on ontology-based documents classification have some drawbacks on precision and run-time performance. In order to solve these problems, this paper proposes a novel ontology-based...
The system of arms information extraction based on the ontology, consists of two parts: knowledge base, processing program. It realizes the arms category determination based on text categorization, and realizes the arms object determination based on named entity recognition. It realizes the information extraction according to information extraction rules based on syntax and semantic constraint. It...
Since the emergence of BLOG, it not only represents a new network technology, but also means the beginning of a new life style. How to utilize and mine the BLOG content which contains hidden sentiment and real-time update is a big challenge in the data-mining domain. As most of the existing method for network text's topic mining is achieved through clustering text's topic and label which are labeled...
Battle Management Language emerges to enhance the interoperability among M&S system, C4I system and future robotic forces, by applying an unambiguous, communicable, comprehensive language and data-exchange mechanism to digitize the information transferred within military systems. Both SISO and NATO have noticed its importance and started their research partly cooperatively. Most researchers identify...
Modern product development needs a large number of knowledge contained at all stages of product life cycle. In order to deal with the discrete, heterogeneous expression, scenario dependence of various types of product knowledge, a context-driven knowledge-sharing approach is presented, covering product knowledge modeling, describing and organizing. Through building product knowledge context model,...
Semantic Web technology highly depends on the quality of ontology as it reduces or eliminates conceptual confusion and reuses knowledge. In order to enhance quality of ontology, there is one major problem with lexical representation of ontology. Current lexical representation is term which may have different meanings, i.e., the term is polysemous, this can result in frustrating misunderstanding and...
At present, several feature meta-models have been come up with. However, they can't meet the requirements of dynamic Internet environment or software reuse. This paper proposes a feature meta-model based on ontology. In particular, it can adapt to various types of changes in the dynamic environment and can make design and implementation more convenient than traditional methods. Finally, we give out...
CP-Nets: CP-nets (Condition Preference Nets) is a tool for representing and reasoning with condition ceteris paribus preference statements put forward by Craig Boutilier, but how to represent and realize is not given. In this paper, after introducing some notions and an example of CP-nets, we adopt binary list as a storage structure to represent and store CPTs, and devise an algorithm for ranking...
RIF (Rule Interchange Format) has become W3C's candidate recommendation on rule interchange. To let RIF represent and interchange fuzzy knowledge in the Semantic Web, we propose RIF-FRD (RIF Fuzzy Rule Dialect), a rule interchange format based on fuzzy sets, defining its XML syntax and metamodel. Based on the metamodel, we propose a fuzzy RIF framework-f-RIA (fuzzy Rule Interchange Architecture),...
The main considerations in the existing XML data dependency models are the structural relevancies of XML nodes but not the information relevancies in XML data which derive from the real world. In this paper, we propose an XML data dependency model (XDDM) based on entity segments. Our main objective is to make XML data dependencies in XDDM match the information relevancies derived from the real world.
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