Carefully studied in-situ hybridization Gene expression patterns (GEP) can provide a first glance at possible relationships among genes. Automatic comparative analysis tools are an indispensable requirement to manage the constantly growing amount of such GEP images. We present here an automated processing pipeline for Segmenting, Classification, and Clustering large-scale sets of Drosophila mel...

Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has been focused on developing automatic clustering algorithms or cluster validation methods. The automatic algorithms are known to work well in dealing with clusters of regular shapes, e.g. compact spherical shapes, but may...

Automatic document categorization plays a key role in the development of future interfaces for Web-based search. Clustering algorithms are considered as a technology that is capable of mastering this “ad-hoc” categorization task. This paper presents results of a comprehensive analysis of clustering algorithms in connection with document categorization. The contributions relate to exemplar-based...

Word clustering is important for automatic thesaurus construction, text classification, and word sense disambiguation. Recently, several studies have reported using the web as a corpus. This paper proposes an unsupervised algorithm for word clustering based on a word similarity measure by web counts. Each pair of words is queried to a search engine, which produces a co-occurrence matrix. By cal...

The problem of clustering speakers by their voices is addressed. With the mushrooming of available speech data from television broadcasts to voice mail, automatic systems for archive retrieval, organizing and labeling by speaker are necessary. Clustering conversations by speaker is a solution to all three of the above tasks. Another application for speaker clustering is to group utterances toge...

Although the validation step can appear crucial in the case of clustering adopting fuzzy approaches, the problem of the partition validity obtained by those adopting the hard ones was not tackled. To cure this problem, we propose in this paper fuzzy-hard mapping processes of clustering while benefitting from those adopting the fuzzy case. These mapping processes concern: (1) local and global cl...

The problem of identifying clusters from MIMO measurement data is addressed. Conventionally, visual inspection has been used for cluster identification, but this approach is impractical for a large amount of measurement data. For automatic clustering, the multipath component distance (MCD) is used to calculate the distance between individual multipath components estimated by a channel parameter...

The automatic clustering of chemical compounds is an important branch of chemoinformatics. In this paper the Asymmetric Clustering Index (Aci) is proposed to assess how well an automatically created partition reflects the reference. The asymmetry allows for a distinction between the fixed reference and the numerically constructed partition. The introduced index is applied to evaluate the qualit...

Services are preprocessed based on clustering techniques in the levels of function and similarity of services. Service clustering is modeled by means of the passing value indeterminacy of logic Petri nets. Thus service clustering can be described, and the services with indeterminacy parameters can be modeled formally. Thus service composition is investigated under the classified architecture of...

MOVICAB-IDS has been previously proposed as a hybrid intelligent Intrusion Detection System (IDS). This on-going research aims to be one step towards adding automatic response to this visualization-based IDS by means of clustering techniques. As a sample case of study for the proposed clustering extension, it has been applied to the identification of different network scans. The aim is checking...