PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Morpho Challenge evaluation by information retrieval
Mikko Kurimo, Mathias Creutz and Matti Varjokallio
In: Advances in Multilingual and MultiModal Information Retrieval, 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark, September 17-19, 2008, Revised Selected Papers Lecture Notes in Computer Science . (2009) Springer .

Abstract

In Morpho Challenge competitions, the objective has been to design statistical machine learning algorithms that discover which morphemes (smallest individually meaningful units of language) words consist of. Ideally, these are basic vocabulary units suitable for different tasks, such as text understanding, machine translation, information retrieval (IR), and statistical language modeling. In this paper, we propose to evaluate the morpheme analyses by performing IR experiments, where the words in the documents and queries are replaced by their proposed morpheme representations and the search is based on morphemes instead of words. In this paper, the evaluations are run for three languages: Finnish, German, and English using the queries, texts, and relevance judgments available in CLEF forum. The results show that the morpheme analysis has a significant effect in IR performance in all languages, and that the performance of the best unsupervised methods can be superior to the supervised reference methods.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Natural Language Processing
Speech
Information Retrieval & Textual Information Access
ID Code:6060
Deposited By:Mikko Kurimo
Deposited On:08 March 2010