This paper describes Armil, a meta-search engine that groups the Web snippets returned by auxiliary search engines into disjoint labelled clusters. The cluster labels generated by Armil provide the user with a compact guide to assessing the relevance of each cluster to his/her information need. Striking the right balance between running time and cluster well-formedness was a key point in the de...

This dissertation studies the problem of clustering objects represented by relational data. This is a pertinent problem as many real-world data sets can only be represented by relational data for which object-based clustering algorithms are not designed. Relational data are encountered in many fields including biology, management, industrial engineering, and social sciences. Unlike numerical ob...

Modern banks have shifted their function as purely administrative, economic and industrial entities into socio-political institutions that must be sensitive to the surrounding environment. This function has always been neglected. This study was conducted based on primary, secondary, and tertiary data and reviews the full text of 75 studies selected from more than 245 studies. The selected elect...

prediction, diagnosis, recovery and recurrence of the breast cancer among the patients are always one of the most important challenges for explorers and scientists. nowadays by using of the bioinformatics sciences, these challenges can be eliminated by using of the previous information of patients records. in this paper has been used adaptive nero fuzzy inference system and data mining techniqu...

Recent work has pointed towards the possibility that industries are not tied to their specific urban location as much as to their linkages with particular types of infrastructure and to their social and economic networks. Industries have similar clustering patterns even in very different cities. Using Bureau of Labor Statistics data, we conducted GIS analysis to compare Los Angeles and New York...

Article history: Received 24 February 2009 Revised 25 March 2009 Accepted 25 March 2009 In this work, we for the first time study the inter-industrial clustering behaviors of integrated circuit (IC) industry fromTaiwan toChinavia amountof foreigndirect investment (FDI). According to themutual dependence among IC design,manufacturing and packaging-and-testing industries, Lotka–Volterra model is ...

In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy ...

1 Graduate Research Assistant. 2 Distinguished Professor of Industrial & Manufacturing Engineering and Member ASME. 3* Professor of Mechanical and Industrial Engineering and Member ASME. Corresponding Author. Email: [email protected]. Phone/fax: (814) 863-7136/4745. ABSTRACT In mass customization, data mining can be used to extract valid, previously unknown, and easily interpretable information from...

Document classification for text, images and other applicable entities has long been a focus of research in academia and also finds application in many industrial settings. Amidst a plethora of approaches to solve such problems, machine-learning techniques have found success in a variety of scenarios. In this paper we discuss the design of a machine learning-based semi-supervised job title clas...