Discovering Unknown Patterns in Free Text

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, this data is not overtly structured like the standard, mainly numerical, data in relational databases. Parallel to data mining, which finds new patterns and trends in numerical data, text mining is the process aimed at discovering unknown patterns in free text. Owing to the importance of competitive and scientific knowledge that can be exploited from these texts, “text mining has become an increasingly popular and essential theme in data mining” (Han & Kamber, 2001, p. 428). Text mining is an evolving field and its relatively short history goes hand in hand with the recent explosion in availability of electronic textual information. Chen (2001, p. vi) remarks that “text mining is an emerging technical area that is relatively unknown to IT professions”. This explains the fact that despite the value of text mining, most research and development efforts still focus on data mining using structured data (Fan et al., 2006). In the next section, the background and need for text mining will be discussed after which the various uses and techniques of text mining are described. The importance of visualisation and some critical issues will then be discussed followed by some suggestions for future research topics.