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User requirements obtained through text data mining are very important to improve the competitiveness of enterprises. In this paper an algorithm of acquiring user requirements in machinery products by using text association rule is proposed. In the algorithm, the user requirement documents are represented by vector space model. The feature words matrix is obtained by transposing the documents matrix...
In the information retrieval technology based on vector space model, represent the Web documents with the vector space model, take the Indexed term weight as a main basis carry on the similarity computation between the user query and Web documents, and sorting query results according to the similarity size. In this paper, adjusted Indexed term weight with the position weighting factor, considering...
Vector space model is commonly used in the formal representation on text, but this approach would not highlight the features which play a key role in the text contents. An improved feature selection method based on key words was proposed, which uses text structural information and mutual information theory to extract key words on text content. Through using support vector machine (SVM) classifier...
This paper uses Vector Space Model to represent topic, and focuses on the creation of the model. Based on the analysis of the characteristics of the English news stories, the paper proposed two methods to improve the topic's representation. Firstly, we propose a news story-oriented feature extraction algorithm based on the combination of word analysis and the location characteristic of the news stories...
According to the high-dimensional sparse features of the storage of the textual document, this paper puts forward a novel model through 3-dimensional space to express text data, in this model, one dimension registers the count of feature words, another denotes the part of speech of the feature words, and the third one records the count of textual documents, that is, the 3-dimensional space model expresses...
In recent years several models have been proposed for text categorization. Within this, one of the widely applied models is the vector space model (VSM), where independence between indexing terms, usually words, is assumed. Since training corpora sizes are relatively small - compared to ap infin what would be required for a realistic number of words - the generalization power of the learning algorithms...
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