Application Of Clustering Algorithm Of Web Text Mining In Gansu Province Poverty Alleviation In The Net

The demand is the mother of invention. In recent years, data mining was aroused great concern of the industry, the main reason users an urgent need to produce large amounts of data into useful information and knowledge, and access to information and knowledge are widely used in business management, production control, market analysis, engineering and other fields of scientific exploration. The birth of Web2.0has accelerated this process, it is compared to a new class of Web1.0Internet applications collectively, it is more focus on user interaction. In the Web1.0era, users only website content viewer, in the Web2.0era, users not only the site’s content viewer, is the maker of the site content, by passively receiving Internet information to take the initiative to create the development of Internet information this shows that the Internet humane. However, a new problem arising from this, the amount of information jumped from which people access information and knowledge is becoming increasingly difficult to rely solely on a single means can not meet the need. So, how to solve this problem, the repository of vast amounts of information in the Internet better able to provide services for the production of human life, has become the years many experts and scholars fought in one direction, thus the birth of a new term:Web text data miningThe Web text data mining is a sub-item of Web data mining research. It can classify the Web resources on the Internet. It also can help Internet users to quickly locate and extract the knowledge which they need, in order to improve the efficiency of getting Web information and gain the valuable information promptly.This paper studies and analyse the Web information by using Web text mining technology in order to achieve the essence of Web text information extractionAt the same time, it focuses on Web text mining technology. And detailedly design the Web text mining clustering algorithm improvement and its realization.The main research in this paper includes:1. Give an introduction about the background of Web text mining and it analysis background and current situation of Web text mining research, and discusses about the significance of Web text mining.2. Give an detail introduction about the key technologies in the procedure of using Web text mining, such as the calculation method of the weight, Chinese word segmentation, discovery and extraction methods of Web text feature and so on.3. Give an introduction about several commonly algorithms of the Web text classification and clustering, for example, Naive Bayes method, KNN nearest neighbor, SOM self-organizing map algorithm and K-means algorithm. And study the theory of K-means algorithm and genetic algorithm and their advantages and disadvantages. Propose the algorithms based on K-means clustering algorithm and genetic algorithms, and do an experiment to test the feasibility of the algorithm.