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Data in the real world is seldom complete. Occlusions or temporally unavailable sensors often lead to situations where incomplete data is presented for analysis. Approaches to handle incomplete data have been proposed using neural networks such as fuzzy ARTMAP and back propagation. In this paper we propose a novel approach extending the unsupervised neural network based clustering technique called...
In this article we present a 2D cellular automaton (Class_AC) to solve a problem of text mining in the case of unsupervised classification (clustering). Before to experiment the cellular automaton, we vectorized our data indexing textual documents from the database REUTERS 21,578 by the approach of N-grams. The cellular automaton that we propose in this paper is a grid cell structure with a flat neighborhood...
Topic discovery described here is used to determine the topic that a document or a segment discusses. It is very important for some applications of natural language processing (NLP), such as information retrieval/extraction, summarization and topic analysis etc. The paper extracts topic words based on Shannon information, in which latent Dirichlet allocation (LDA) is employed to represent word distribution...
Clustering technology is the core technology of text mining. Through text clustering, a large number of text messages can be divided into several meaningful classes or clusters. According to the features of Chinese documents, this paper designs and implements the Chinese Text Clustering System to perform automatic clustering of Chinese documents. Firstly, this system will carry out Chinese word automatic...
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