Based On The Hot Topic Automatically Discover Web Site Search Engine Optimization (seo)

Search engines plays an important role when getting information from internet, has been widely used. Search engine optimization refers to optimizing Web pages, site keywords, site structure and improves the user experience and other factors make the site comply with search engine rules, and make the site have the nice ranking in search engine result. Content optimization is one of the main trends of the future, but also search engine has been advocated.Considering that the deepening of the Web2.0application, the way people participate in the network constantly changing, that was not only a participant, but also has slowly transformed into the call by, more and more popular term, initiated by the public, popular from the public.So as to bring a new idea that hot topic discovery on the platform on social networks, so as to bring a wealth of words for search engine optimize.Hot topics before the basic network is based on clicks, or number of comments to be reprinted, the content of comments and echo the nature of the topic itself considered relatively small. In this paper, taking into account the hot topics that affect the degree of comment is an important factor, while noting that the content of the comments and topic relevance, then a relatively low degree of correlation for noise filtering the comments, the comments to the remaining hot spots on the calculation, thus found to be a hot topic of social networks.In addition, as larger than a hot topic, hot topics found in the formation of this paper, based on the combined channel classification algorithm to optimize the formation of opinions will be very meaningful to the user. In the classification of technical considerations to the vector space model, feature items empowerment, feature selection, classifier construction, etc. In this paper, previous studies on the vector space model based on the existing right of re-analysis of the algorithm and classification algorithm, and finally improved use of TF-IDF algorithm with Rocchio weight characteristics to achieve a classification method, the end result proved to be effectiveThis design process and more factors to consider automation to reduce manual intervention, improve efficiency factor, which in the search engine optimization, there is a high practical value.