Genre as noise: noise in genre

Given a specific information need, documents of the wrong genre can be considered as noise. From this perspective, genre classification helps to separate relevant documents from noise. Orthographic errors represent a second, finer notion of noise. Since specific genres often include documents with many errors, an interesting question is whether this “micro-noise” can help to classify genre. In this paper we consider both problems. After introducing a comprehensive hierarchy of genres, we present an intuitive method to build specialized and distinctive classifiers that also work for very small training corpora. We then investigate the correlation between genre and micro noise. Using special error dictionaries, we estimate the typical error rates for each genre. We finally test if the error rate of a document represents a useful feature for genre classification.

• Type: Journal
• Year: 2007
• Where: IJDAR
• Authors: Andrea Stubbe, Christoph Ringlstetter, Klaus U. Schulz
• Keywords: Document, Error Rate, IJDAR 2007, Wrong Genre