A New Keywords Method to Improve Web Search

Abstract

In order to let people be able to get information from the Web easily, search engine comes into being and continues to grow and develop. People begin to explore all kinds of ranking algorithms and try to give user a good result list. However, the expression format of the web information and user queries are very simple, which results in the difficulty of determining the relevance between user queries and web information. The success and popularity of social network systems, such as del.icio.us, Face book, etc., have generated many interesting problems to the research community. This gives us a new viewpoint on how to improve the quality of information retrieval. The contributions of our research are twofold. First, the existing ranking algorithms of search engine are classified. And we extend expression of queries by “keyword and ”, instead of keywords only. Second, a new ranking algorithm based on user feedback and semantic tags is proposed, and it is also compared with Google by several evaluation methods.