A Frame Work for Text Mining using Learned Information Extraction System

Text mining is a very exciting research area as it tries to discover knowledge from unstructured texts These texts can be found on a computer desktop intranets and the internet The aim of this paper is to give an overview of text mining in the contexts of its techniques application domains and the most challenging issue The Learned Information Extraction LIE is about locating specific items in natural-language documents This paper presents a framework for text mining called DTEX Discovery Text Extraction using a learned information extraction system to transform text into more structured data which is then mined for interesting relationships The initial version of DTEX integrates an LIE module acquired by an LIE learning system and a standard rule induction module In addition rules mined from a database extracted from a corpus of texts are used to predict additional information to extract from future documents thereby improving the recall of the underlying extraction system Applying these techniques best results are presented to a corpus of computer job announcement postings from an Internet newsgrou

Maximizing Computational Profit in Grid Resource Allocation Using Dynamic Algorithm

Grid computing, one of the most trendy phrase used in IT, is emerging vastly distributed computational paradigm. A computational grid provides a collaborative environment of the hefty number of resources capable to do high computing performance to reach the common goal. Grid computing can be called as super virtual computer, it ensemble large scale geographically distributed heterogeneous resources. Resource allocation is a key element in the grid computing and grid resource may leave at anytime from grid environment. Despite a number of benefits in grid computing, still resource allocation is a challenging task in the grid. This work investigates to maximize the profits by analyzing how the tasks are allocated to grid resources effectively according to quality of service parameter and gratifying user requisition. A fusion of SS-GA algorithm has introduced to answer the above raised question about the resource allocation problem based on grid user requisition. The swift uses genetic algorithms heuristic functions and makes an effective resource allocation process in grid environment. The result of proposed fusion of SS-GA algorithm ameliorates the grid resource allocation