Study And Implement On Views Crawling And Demand Matching In Precision Marketing

With the rapid development of internet, more and more traditional marketing has been transform to precision marketing, and precision marketing has slowly become a trend. Especially in recent years, with the diversification of customer needs, manufactures constantly adjust based on the change strategies to adapt to market demand, but also has the development of precision marketing as the only way. Precision marketing is to break through the precise positioning of the pattern of traditional marketing can only be characterized, at the same time by means of advanced technological means to ensure communication with the customer's personalized service system of a low-cost marketing methods.Precision marketing analysis involves crawling, pre-processing, word, syntax analysis, data mining, demand matching technology, but research in this paper is the views crawling and demand matching technology, these two technologies in precision marketing occupy a very important position. Views crawling is the application of web crawling to get what we want to take the information on the web page; demand matching is when we have a user views or needs, we can crawl according to this view or theme, to be able to meet customer needs information, then feedback to the user for their selection decisions. Of course, after we take for web crawling, to get the user's point of view or needs to go through a series of processing, including word, syntax analysis, data mining, etc. In this article, these are not described in detail.This paper first made a probably introduce of precision marketing, and at the same time leads to the point of views crawling and demand matching. Then dicuss the whole system program, design of the system's overall architecture, and each part is described. After the system began to focus on the architecture point of views crawling and demand matching.For the views crawling, the main application is web crawling knowledge, but also related to the information pre-processing. Because the network on the web crawling theory and technology is more mature, so in this article did not go out programming, but the means to achieve the current viewpoint crawling software. By a given URL address, whichever is content to crawl and links on the page's URL, then go through the information pre-processing, text messages will be saved for analysis, syntax analysis and other analytical needs.In the demand matching, to achieve this mainly of two parts:subject crawling and needs feedback. Compared to the general theme of web crawling, the main difference of subject crawling lies in its pages relevance and links relevance, while the relevance of these two is the key theme of crawling. Now the domestic technology, while crawling a lot of research, but there is not a viable technology, mostly in the theoretical research. In this theme, after raise the subject crawling, the pages relevance and links relevance are also related to a bit detail, and the use of a simple Java technology implementation. The demand for this part of the feedback, the main emphasis is information feedback, after the theme content crawling process, get the information to meet customer needs, and then feedback to the user. In this feedback, this paper mainly by E-mail message is sent to achieve, although a variety of feedback channels, but through the mail is the easiest, most convenient and . efficient. In its implementation, but also through the Java programming language,and also gives an Andriod system implementation, will be sent by e-mail package, then call the Andriod system comes with email functions to achieve.Because the precision marketing is a great system engineering, and the technology of subject crawling is not very mature,and coupled with limited capacity, so this is there are still some shortcomings need to further study after study. In the realization of the subject crawling, should seek to achieve a more practical approach to preparing for a structured and powerful software. Feedback needs to achieve, also need to take different points of view target to climb different feedback channels were designed. So in this part of the demand matching, but also requires further study.