| Clustering and feedback have been used in information retrieval to improve the effectiveness of retrieving relevant documents. In this thesis, we investigate the retrieval effectiveness from various document collections in presence of both clustering and feedback. More precisely, we apply a clustering algorithm to an initial run of our queries to choose appropriate clusters for feedback. The clustering and feedback are done automatically. |
