Marked Social Search Engine Optimization

As a very important technique of web2.0, the most prominent contribution of social annotations is that it successfully makes web users turn from being simplex information acceptors to active information promulgators and profoundly influence the information transmitting mode on the web. With tags, other websites or users can conveniently classify the information. The function of tags is similar to which of the keywords in search technique, it's the personalized description to information. In the usual situation, it's very hard to carry through whole-length text retrieval (only those powerful search engines can constrainedly achieve), so the annotated information are more easily transmit than the un-annotated. Web users describe the information and create easy retrieval by the action of annotating, and they can look for the information which they are interested in by the description of tags. Because of the organic combination of polymerization content technique and annotation technique, standardized information interface reduce the cost of information transmitting and re-process, consequently, reduce the cost of time and economy when people want to acquire personalized information. With social bookmarks, we can use multi-tags as keywords to annotate the websites and webpage(be point to by bookmarks on the web ) which we are fond of, and share them with other web users. The function of social annotations is similar to classifying search engines, the difference between them is that the creators of social annotations are normal web users rather than powerful corporations. So it has more actual effect and classify more accurately.With the influence extension of web 2.0 technique, the resource which can be digged on web is more abundance. Utilizing social annotations to optimize the retrieval efficiency of search engines can not only quickly and accurately go to the information which the users need but also satisfy the users'need of personalized information. Thereby, it obviously improves the search experience of the users. So the research on this aspect has significant commercial value.The major work in this paper include the following three parts:(1) the research based on the content of social annotationIn this paper, we judge the content of social annotations mainly by the semantic of tags. By comparing the relation between tags,tags and webpage, we measure the semantic similarity of them. And commend to the users according to this semantic similarity, consequently, achieve the aim to optimize search engines.(2) the research based on the significance of social annotationThere are many aspects to scale the significance of social annotation. In this paper, we mainly consider the time factor. We analyze and utilize the time factor of the new data source"tag"to weigh the importance and novelty of tags and propose a new algorithm named TagRank based on social annotations for page ranking. This algorithm digs the annotation behavior of the web users, calculates the"heat"of the tags, consequently, it can response the true quality of tags more externally and improve the veracity of page ranking. The experiment shows that our algorithm works effectively.(3) the research based on the personalization of social annotationThe research based on the personalization of social annotation doesn't need the active participation of users, but by the filtration of co-tag data, we can cluster the users'annotation data and acquire their preference to classify tags in level, consequently, get a characteristic about the user, and purposefully commend to the user according to this characteristic, finally provide personalized service to the user successfully.