Personalized Profile Based Search Interface With Ranked and Clustered Display

Abstract

We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list optionally based on the user’s profile. The system also allows the user to give positive or negative feedback on the documents, clusters and indices. The architecture allows different algorithms for each of the features to be plugged-in easily, i.e. various clustering, indexing and relevance feedback algorithms, and profiling methods.