Linguistically-Adapted Structural Query Annotation for Digital Libraries in the Social Sciences
Caroline Brun, Nikolaos Lagos, Vassilina Nikoulina
Query processing is an essential part of a range of applications in the social sciences and cultural heritage domain. However, out-of-the-box natural language processing tools originally developed for full phrase analysis are inappropriate for query analysis. In this paper, we propose an approach to solving this problem by adapting a complete and in-tegrated chain of NLP tools, to make it suit-able for queries analysis. Using as a case study the automatic translation of queries posed to the Europeana library, we demon-strate that adapted linguistic processing can lead to improvements in translation quality.
13th Conference of the European Chapter of the Association for Computational Linguistics, Avignon, France, April 23-27, 2012.