A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
It provides an overview for researchers or practitioners interested in text mining, but is incremental as it summarizes existing methods.
The paper surveys fundamental text mining tasks and techniques, such as classification and clustering, to extract meaningful information from unstructured text, without presenting new results or numbers.
The amount of text that is generated every day is increasing dramatically. This tremendous volume of mostly unstructured text cannot be simply processed and perceived by computers. Therefore, efficient and effective techniques and algorithms are required to discover useful patterns. Text mining is the task of extracting meaningful information from text, which has gained significant attentions in recent years. In this paper, we describe several of the most fundamental text mining tasks and techniques including text pre-processing, classification and clustering. Additionally, we briefly explain text mining in biomedical and health care domains.