Semantic Classification and Co-occurrences: A Method for the Rules Production for the Information Extraction from Textual Data

Abstract

Information extraction is a field of computer science research which explores the problem of detecting and retrieving desired information from textual data. This paper proposes a two-steps method that enables the detection of relevant information within a corpus of textual data. The first phase consists of observing the most recurrent structures through the study of textual co-occurrences and collocations, while the following phase consists of deriving rules from these structures which make it possible to create an inventory of all the expressions that identify a particular concept of interest, that is, the desired information.