Etude comparative de l’efficacité du dépistage de l’information dans des manuscrits médiévaux

This paper presents, evaluates and compares the effectiveness of information retrieval (IR) for medieval manuscripts when facing with noisy texts. The corpus used in our experiments is based on a well-known medieval epic poem written in Middle High German dating to the thirteenth century (Parzival). An error-free transcription of the poem was created manually and made available by experts. This error-free transcription represents our baseline that we used to assess the performance levels. In practice, the document noise could be caused by different sources (e.g., spelling variations due to non-normalized medieval text, recognition mistake). To overcome these difficulties, we suggest several query expansion strategies, hence allowing some form of spelling variation between the requests and the searchable items. To analyze these performances under several conditions, we have evaluated five IR models, three forms of stemming and three text representations. We show that incorporating the maximum spelling variation possibilities in the query expansion process does not produce the best results, while a wiser and more conservative approach of involving expansion terms yields better performance levels.