Identification of distinct clusters of documents in text collections has traditionally been addressed by making the assumption that the data instances can only be represented by ...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
The k-means algorithm with cosine similarity, also known as the spherical k-means algorithm, is a popular method for clustering document collections. However, spherical k-means ca...
In this paper we explore the effectiveness of three clustering methods used to perform word image indexing. The three methods are: the Self-Organazing Map (SOM), the Growing Hiera...
We develop a new algorithm for clustering search results. Differently from many other clustering systems that have been recently proposed as a post-processing step for Web search ...
The paper describes the initial results of applying Latent Semantic Analysis (LSA) to program source code and associated documentation. Latent Semantic Analysis is a corpus-based ...