Applying Data Mining Techniques in Text Analysis
Helena Ahonen-Myka · 1997
A number of recent data mining techniques have been targeted especially for the analysis of sequential data. Traditional examples of sequential data involve telecommunication alarms, Www log files, user action registration for Hci studies, or any other series of events consisting of an event type and a time of occurrence. Text can also be seen as sequential data, in many respects similar to the data collected by sensors, or other observation systems. Traditionally, texts have been analysed using various information retrieval related methods, such as full-text analysis, and natural language processing. However, only few examples of data mining in text, particularly in full text, are available. In this paper we show that general data mining methods are applicable to text analysis tasks under certain conditions. Moreover, we present a general framework for text mining. The framework follows the general Kdd process, thus containing steps from preprocessing to the utilization of the results...