N-Gram Morphemes for Retrieval
Paul McNamee, James Mayfield · CLEF (Working Notes) · 2007
Stemming, an approximation to morphological analysis, is a commonly used technique to improve performance in information retrieval systems. In the MorphoChallenge 2007 evaluation we applied a simple zero-knowledge technique that is based on frequency counts rather than machine learning. Our method is based on substituting a single xed-length substring for each word that appears in documents or queries. We hope to discover whether this method, which has been used in previous IR evaluations with good eect, will be as eective for the information retrieval task as the unsupervised methods used by other participants. It should be emphasized that out submission was not a credible attempt to learn morphology and thus is not expected to perform well in the morphology induction task.