Linguistically-Adapted Structural Query Annotation for Digital Libraries in the Social Sciences - Naver Labs Europe
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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.

NAVER LABS Europe
NAVER LABS Europe
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