Literature Characterization and Similarity Retrieval Based on Hierarchical Clustering

The growing number of literature in journals database raises a new and challenging search problem: locating desired literature. Traditional keyword search is insufficient: the specific literature users require is possibly not captured. We introduce a new algorithm of hierarchical clustering. With this algorithm, we cluster the keywords into a concept tree, then we turn every literature into an induced tree. We propose a new method for theses retrieval, which based on concept similarity. This method improves in recall and precision.