TABLE OF CONTENTS Moty Ben-Dov
MDX University, London
Ronen Feldman
Bar-Ilan university, Ramat-Ga n
| Abstract | Text Mining is the automatic discovery of new, previously unknown information, by automatic analysis of various textual resources. Text mining starts by extracting facts and events from textual sources and then enables forming new hypotheses that are further explored by traditional Data Mining and data analysis methods. In this chapter we will define text mining and describe the three main approaches for performing information extraction. In addition, we will describe how we can visually display and analyze the outcome of the information extraction process. |
| Keywords: | text mining, content mining, structure mining, text classification, information extraction, Rules Based Systems. |
The information age has made it easy for us to store large amounts of texts. The proliferation of documents available on the Web, on corporate intranets, on news wires, and elsewhere is overwhelming. However, while the amount of information available to us is constantly increasing, our ability to absorb and process this information remains constant. Search engines only exacerbate the problem by making more and more documents available in a matter of a few key strokes; So-called "push" technology makes the problem even worse by constantly reminding us that we are failing to track news, events, and trends everywhere. We experience information overload, and miss important patterns and relationships even as they unfold before us. As the old adage goes, "we can't see the forest for the trees."
Text-mining (TM), also known as Knowledge discovery from text...
