Research paper on search technology:

Iterative Filtering of Retrieved Information to Increase Relevance

Efforts have been underway for years to find more effective ways to retrieve information from large knowledge domains. This effort is now being driven particularly by the Internet and the vast amount of information that is available to unsophisticated users. In the early days of the Internet, some effort involved allowing users to enter Boolean equations of search terms into search engines, for example, rather than just a list of keywords. More recently, effort has focused on understanding a user’s desires from past search histories in order to narrow searches. Also there has been much effort to improve the ranking of results based on some measure of relevancy. This paper discusses using iterative filtering of retrieved information to focus in on useful information. This work was done for finding source code correlation and the author extends his findings to Internet searching and e-commerce. The paper presents specific information about a particular filtering application and then generalizes it to other forms of information retrieval.

Paper given at the 11th World Multi-Conference on Systemics, Cybernetics and Informatics, July 11, 2007.