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Generating 3D virtual scene plays an essential role in computer graphics and animation. However, manual 3D scene construction is time-consuming and requires enormous efforts from professionals. Recently, more and more researchers shift their interests into the field of automatic scene generation. Although it hardly yields results as good as manual construction, automatic scene generation largely speeds...
We consider the possibility to avoid duplication of information to the user in the search of information about the object search. This result is achieved through ongoing evaluation of all documents are search based utility. According to the value selected the best parts of the text, which later included in the structured document and is the result of information search.
In this paper, we present an automatic terminology extraction approach for Chinese multi-word terms. In this term extraction system, besides five linguistic rules acquired from an available term list by some machine learning methods, two statistical strategies are involved: a termhood measure based on the term distribution variation, and a unithood measure adopting the left and right entropy method...
An important problem in text mining is the automatic extraction of semantic relations. The paper provides a domain independent method for automatic extraction of part-whole relations in Chinese corpusa. The method consists of there phases. First, a set of lexico-syntactical patterns for part-whole relations are designed using known pairs of concepts encoding part-whole relations as seeds, and manually...
Style-based text authorship identification extracts features from authorship-known texts, constructs classifier and then identifies disputed texts. Authorship identification belongs to the domain of style classification and is a branch of text classification. In contrast with text classification which deals with the content of texts, authorship identification focuses on the form property of texts...
Sem@ntica is a system for extracting the information contained in collections of documents into a knowledge base. It combines high quality conventional named entity analysis with an ontology class labeling capability for open class words. The ontology comprises an upper ontology and one or more domain ontologies. The system has tools for rapidly designing the ontology and mapping segments of Word...
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