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Latent Dirichlet allocation (LDA) has been widely used for analyzing large text corpora. In this paper we propose the topic-weak-correlated LDA (TWC-LDA) for topic modeling, which constrains different topics to be weak-correlated. This is technically achieved by placing a special prior over the topic-word distributions. Reducing the overlapping between the topic-word distributions makes the learned...
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...
A common strategy to assign keywords to documents is to select the most appropriate words from the document text. One of the most important criteria for a word to be selected as keyword is its relevance for the text. The tf.idf score of a term is a widely used relevance measure. While easy to compute and giving quite satisfactory results, this measure does not take (semantic) relations between words...
In the research of modern linguistics, word frame information, which is significant in the study of Chinese information processing, draws more researchers' attention. Its distinction between word argument and auxiliaries plays an important part in the precision of syntactic analysis, elimination of semantic ambiguities and semantic role labeling. Therefore, the study of categorization frame information...
The traditional single-document automatic abstracting based on statistical extracts a number of sentences sorted by the importance of the sentences to form summarization, which often neglects semi important topics of the text, and makes the summarization not completely. To overcome this shortcoming, the paper presents an improved k-means algorithm to divide topic in the analysis of text structure...
Lexical Cohesion is one of the important features in text processing for analyzing document structure and improving the accuracy of text processing. We present a hierarchial graph based model to measure cohesion by grouping lexically cohesive units together in a text. Latent semantic analysis is used to construct a relational graph to uncover the hidden semantics from the text by discovering new relations...
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