From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Data And Text Mining: A Business Application Approach
Data And Text Mining: A Business Application Approach
Newsmap: a knowledge map for online news
Decision Support Systems - Special issue: Collaborative work and knowledge management
Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A text mining approach for automatic construction of hypertexts
Expert Systems with Applications: An International Journal
Using text classification and multiple concepts to answer e-mails
Expert Systems with Applications: An International Journal
Applying text and data mining techniques to forecasting the trend of petitions filed to e-People
Expert Systems with Applications: An International Journal
Applying VSM and LCS to develop an integrated text retrieval mechanism
Expert Systems with Applications: An International Journal
A multi-classifier system for text categorization
Proceedings of the 2011 ACM Symposium on Research in Applied Computation
Applying text-mining to personalization and customization research literature - Who, what and where?
Expert Systems with Applications: An International Journal
Improving user experience with case-based reasoning systems using text mining and Web 2.0
Expert Systems with Applications: An International Journal
IT innovation adoption by enterprises: Knowledge discovery through text analytics
Decision Support Systems
How to identify the trends of services: GTM-TT service map
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Text mining is a semi-automated process of extracting knowledge from a large amount of unstructured data. Given that the amount of unstructured data being generated and stored is increasing rapidly, the need for automated means to process it is also increasing. In this study, we present, discuss and evaluate the techniques used to perform text mining on collections of textual information. A case study is presented using text mining to identify clusters and trends of related research topics from three major journals in the management information systems field. Based on the findings of this case study, it is proposed that this type of analysis could potentially be valuable for researchers in any field.