1 In this paper, we present a study for extracting and aligning paraphrases in the context of Sentence Compression. First, we justify the application of a new measure for the automatic extraction of paraphrase corpora. Second, we discuss the work done by (Barzilay & Lee, 2003) who use clustering of paraphrases to induce rewriting rules. We will see, through classical visualization methodologies...

Automatic attribute selection is a critical step when using Formal Concept Analysis (FCA) in a free text document retrieval framework. Optimal attributes as document descriptors should produce smaller, clearer and more browsable concept lattices with better clustering features. In this paper we focus on the automatic selection of noun phrases as document descriptors to build an FCA-based IR fra...

The customer load profile clustering method is used to make the TDLP (Typical Daily Load Profile) to estimate the quarter hourly load profile of non-AMR (Automatic Meter Reading) customers. This study examines how the repeated clustering method improves the ability to discriminate among the TDLPs of each cluster. The k-means algorithm is a well-known clustering technology in data mining. Repeat...

Identifying specific CT-image regions is an important process in medical diagnosis. Clustering is a simple and useful means for automatic image segmentation. However, clustering results vary with the features of image pixels and the settings of parameters of the clustering methods. This study compares the results of CT image segmentation using FCMbased clustering algorithms running with intensi...

The ProtoNet site provides an automatic hierarchical clustering of the protein space. The clustering is based on an all-against-all BLAST similarity test. With this similarity measure we proceed to perform a continuous bottom-up clustering process by applying alternative rules for merging clusters. The outcome of this clustering process is a classification of the input proteins into a hierarchy...