Research On Contextual Topic Analysis Based On Softman And Its Application

The development of Internet social network will promote Internet evolvefrom the network of information to the network of person. And software will playthe role of virtual entity of people to participate activities in the social network,where personal data space is mapped into the virtual brain of Softman. In the newnetwork environment, the monitoring of Internet information and topic analysisrelies on topic patterns that each softman has for different contexts, which is alsocalled personal and contextual topic model.The dissertation is based on the research of National Science Foundation ofChina (The Research of Cross-media Data Mining on Emergency Information, No.91024001), Beijing Natural Science Foundation (The Research of Data Mining onTourism Emergency Information and Intelligent Prediction, No.4082021), andBeijing Natural Science Foundation (The Research of Fusion of 'Softman' andLinux, No.:4072018). With the Internet information monitoring of emergency andtourism information service as the application background, the theory ofSoftman's contextual topic modeling, topic pattern extraction and cross-mediatopic analysis is studied in the dissertation. And the solutions of criticaltechnologies are also proposed and implemented in the application systems. Mainresults of the dissertation can be concluded as follows.1) A contextual topic model applied in Softman based Internet social networkmonitoring environment is presented in this dissertation. And the formal definitionof context is given to describe the background of the topic. The cognition ofsoftman is implemented by establishing mixture contextual topic model. Thecontextual model is established by introducing contextual variables into theprobabilistic topic model, and the changes of topic in content and intensity underdifferent scenarios is analyzed through conditional distribution of the topic andother contexts. Moreover, the prior knowledge is also incorporated into the modelthrough a general component. Effectiveness of the model is verified by theexperiments of text and cross-media topic analysis.2) A spatiotemporal topic analysis method is presented by introducing spatioand temporal information into the contextual topic analysis framework. In thisway, the distribution of mixture of subtopics is associated with spatiotemporalcontext to describe the lifecycle and strength of topics. And an improved temporal clustering and EM algorithm is given to achieve contextual topic discovery andtracking. Experiment's results show that this method is better than that in the wordspace.3) An automatic topic labeling method is presented to make the probabilistictopic model become understandable for ordinary users. An associated topic wordsextraction method based on semantic classification is proposed to build candidatelabel set. And a label selection method is also given to automatically select topicwords with high semantic coverage and distinction to explain the characteristicsof various contextual models. Experiment's results show that this method is betterthan that of high probability topic word tagging. Especially, for food safety topic,the accuracy is close to that of manual annotation.4) A cross-media topic analysis method using visual topic model is presentedin this dissertation, in which the meaning of the image is described with visualwords. And a visual topic learning algorithm is given to establish relationshipsbetween texts and images by mapping topic of texts to that of images, in whichthe topic of texts is described with visual words to achieve the uniform descriptionand topic modeling of cross-media data. Experiment's results show that thismethod improve the accuracy of topic detection for short text data.5) On the basis of the above research. Food safety information monitoringsystem and intelligent tourism information push and pull system are designed,which are applied to food safety incident monitoring and personal tourisminformation service respectively.This work contributes to topic analysis and monitoring on the increasinglycomplex Internet information. It can be used to discovery hot topics and will dohelp to improve decision making ability or to provide personal informationservice.