QingQiang Wu

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This paper analyses topic segmentation based on the LDA (Latent Dirichlet Allocation) model, and performs the topic segmentation and topic evolution of stem cell research literatures in PubMed from 2001 to 2012 by combining the HMM (Hidden Markov Model) and co-occurrence theory. Stem cell research topics were obtained with LDA and expert judgements made on(More)
A text mining model for topical evolutionary analysis was proposed through a text latent semantic analysis process on textual data. Analyzing topic evolution through tracking the topic different trends over time. Using the LDA model for the corpus and text to get the topics, and then using Clarity algorithm to measure the similarity of topics in order to(More)
In this paper, an oil exploration software is designed, introduced and implementation. The software is based on the procedures of oil exploration and seismic prospecting. In the environment of Microsoft Visual Studio 2008 with the C++ programming language, the standard SEG-Y seismic data is successfully transferred into visible geological sectional view and(More)
The paper presents an authentication system that allows the user to query expansive training certification records for the university student. Firstly, we analyze the requirements of authentication system and come up with feasible solutions on the basis of learning the plan on expansive training to the cultivation of student quality. Before carrying out the(More)
Burst topic detection aims to extract rapidly emerging topics from large volumes of text streams, including scientific literature. Currently there are several burst models and detection algorithms based on different burst definitions, which share the common deficiency that semantic information of topics is not taken into consideration, which results in(More)
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