A Methodological Framework for Dictionary and Rule-based Text Classification

Jennifer Abel, Birger Lantow

Abstract

Recent research on dictionary- and rule-based text classification either concentrates on improving the classification quality for standard tasks like sentiment mining or describe applications to a specific domain. The focus is mainly on the underlying algorithmic approach. This work in contrast provides a general methodological approach to dictionary- and rule-based text classification based on a systematic literature analysis. The result is a process description that enables the application of these technologies on specific problems by guidance through major decision points from the definition of the classification goals to the actual classification of texts.

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