Micro-blog has become an emerging application in the Internet in recent years, and affective computing and sentiment analysis for micro-blog have been a vital research project in computer science, natural linguistics, psychology of human, and other social computing fields. In this paper, firstly, fuzzy clustering theory was introduced and source database for micro-blog was constructed. Then, word similarity computation method based on basic emotion word set of HowNet was used to calculate weights of micro-blog emotion words, and micro-blog emotional lexicon was built. Next, using calculation methods for appropriate sentiment value, the whole micro-blog message's emotional values were obtained. Finally, sentiment values from users in different time periods were selected as original data matrix, using the fuzzy clustering algorithm. The users were classified dynamically; meanwhile, dynamic clustering figure was generated. The best classification was obtained by using F statistics test method, and emotion trend graph was predicted from classification results, to more intuitively analyze emotion changes of user. In this paper, using micro-blog information with affective computing, governments, businesses, or enterprises can get different classification results according to the different needs and take the appropriate measures.
In view of the advantage of combination of agent and web service, introducing agent and web service into distributed data mining, a multi-layer distributed data mining model based on intelligent agent and web service technologies is presented to overcome difficulties of the traditional distributed application technologies such as distribution, heterogeneity, autonomy. This model describes the general framework, the distribution of Agents,the function of agents and web service component.This framework is applied to data mining for gas fields with MAS to improve performance and flexibility of system.Finally, The research results has greatly increased gas-field production safety management level and gained good economic and the social benefit.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.