This document gives brief description about various Punjabi dictionaries that have been developed and text mining techniques. The various text mining techniques are briefly studied and are compared according to different parameters. The best technique is then proposed for developing a text mining model for Punjabi data dictionary. This purposed model can be used to create a dynamic ever updatin...

In this study, a multi-agent web text mining system on the grid is developed to support enterprise decision-making. First, an individual intelligent learning agent that learns about underlying text documents is presented to discover the useful knowledge for enterprise decision. In order to scale the individual intelligent agent with the large number of text documents on the web, we then provide...

Data mining, or knowledge discovery, has recently become a popular research area. Data mining methods have been applied to a wide variety of domains, from supermarket basket data and telecommunication alarm data to the analysis of satellite pictures and human genomes. Surprisingly enough, only a few examples of data mining in text are available. However, considering the amount of existing docum...

Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...

Text Mining is an important step of Knowledge Discovery process. It is used to extract hidden information from not-structured or semi-structured data. This aspect is fundamental because most of the Web information is semistructured due to the nested structure of HTML code, is linked and is redundant. Web Text Mining helps whole knowledge mining process in mining, extraction and integration of u...

Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...

Text Mining is an important step of Knowledge Discovery process. It is used to extract hidden information from notstructured o semi-structured data. This aspect is fundamental because much of the Web information is semi-structured due to the nested structure of HTML code, much of the Web information is linked, much of the Web information is redundant. Web Text Mining helps whole knowledge minin...

Biomedical literatures have been increased at the exponential rate. To find the useful and needed information from such a huge data set is a daunting task for users. Text mining is a powerful tool to solve this problem. In this paper, we surveyed on text mining in Bioinformatics with emphasis on applications of text mining for bioinformatics. In this paper, the main research directions of text ...

Copyright © 2006, Idea Group Inc., distributing in print or electronic forms without written permission of IGI is prohibited. INTRODUCTION A very large percentage of business and academic data is stored in textual format. With the exception of metadata, such as author, date, title and publisher, these data are not overtly structured like the standard, mainly numerical, data in relational databa...

The possibilities for data mining from large text collections are virtually untapped. Text expresses a vast, rich range of information, but encodes this information in a form that is difficult to decipher automatically. Perhaps for this reason, there has been little work in text data mining to date, and most people who have talked about it have either conflated it with information access or hav...