Recently people have relied on the use of web search engines to learn how to accomplish tasks, solve problems and gain information. But in an organization, just using the major search engines such as Google, Yahoo or Bing, sometimes the search results are too varied and lack relevance with the organization's related topics. In this research plan, I propose a framework called the “Adaptive Search Framework” and there is a demo application which called Community Search. It can learn from the users' provided information and adapt itself to choose more relevant and important web pages that are related to the in-organization important topics. I also propose a re-ranking algorithm for search results. The algorithm gives a score based on the importance and popularity inside the organizations. Our preliminary results show that the Adaptive Search Framework can learn and return more topic-relevant results to the organization at the top ranks. It helps users save much time in searching for desired information on the web.
The rest of this research status describes my work in progress on the Adaptive Search Framework.
It is in a research paper format, with introduction, background, the Adaptive Search Framework system description, experiment, discussion, conclusions and future work. There is also a brief list of my awards, papers, and research grants. I hope this material will be helpful to you in understanding my research.