The goal of automatic text summarization is to reduce the size of a document while preserving its content. We investigate a summarization method which uses not only statistical features but also the contextual meaning of documents by using lexical clustering. We present a new method to compute lexical cluster in a text without high cost knowledge resources; the WordNet thesaurus. Summarization ...

In this paper, we propose an automatic PAM (Partition Around Medoids) clustering algorithm for outlier detection. The proposed methodology comprises two phases, clustering and finding outlying score. During clustering phase we automatically determine the number of clusters by combining PAM clustering algorithm and a specific cluster validation metric, which is vital to find a clustering solutio...

Determining optimal number of clusters in a dataset is a challenging task. Though some methods are available, there is no algorithm that produces unique clustering solution. The paper proposes an Automatic Merging for Single Optimal Solution (AMSOS) which aims to generate unique and nearly optimal clusters for the given datasets automatically. The AMSOS is iteratively merges the closest cluster...

Most modal parameter estimation techniques utilize Stabilization/Consistency Diagram as a tool for distinguishing between physical system modes and mathematical modes. However, this process results in giving several estimates of the same mode and the task of choosing one estimate over others is left to the user. This task is highly judgmental, with user expertise playing a big role as to which ...

Analyzing protein sequence data becomes increasingly important recently. Most previous work on this area has mainly focused on building classification models. In this paper, we investigate in the problem of automatic clustering of unlabeled protein sequences. As a widely recognized technique in statistics and computer science, clustering has been proven very useful in detecting unknown object c...

We propose a decentralized algorithm for organizing an ad hoc sensor network into clusters. Each sensor uses a random waiting timer and local criteria to determine whether to form a new cluster or to join a current cluster. The algorithm operates without a centralized controller, it operates asynchronously, and does not require that the location of the sensors be known a priori. Simplified mode...

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Automatic text summarization has emerged as a technique for accessing only to useful information. In order to known the quality of the automatic summaries produced by a system, in DUC 2002 (Document Understanding Conference) has developed a standard human summaries called gold collection of 567 documents of single news. In this conference only five systems could outperforms the baseline heurist...

Finding the optimal number of clusters has remained to be a challenging problem in data mining research community. Several approaches have been suggested which include evolutionary computation techniques like genetic algorithm, particle swarm optimization, differential evolution etc. for addressing this issue. Many variants of the hybridization of these approaches also have been tried by resear...