An Unsupervised Query Rewriting Approach Using N-gram Co-occurrence Statistics to Find Similar Phrases in Large Text Corpora

Hans Moen, Laura-Maria Peltonen, Henry Suhonen, Hanna-Maria Matinolli, Riitta Mieronkoski, Kirsi Telen, Kirsi Terho, Tapio Salakoski, Sanna Salanterä


Abstract
We present our work towards developing a system that should find, in a large text corpus, contiguous phrases expressing similar meaning as a query phrase of arbitrary length. Depending on the use case, this task can be seen as a form of (phrase-level) query rewriting. The suggested approach works in a generative manner, is unsupervised and uses a combination of a semantic word n-gram model, a statistical language model and a document search engine. A central component is a distributional semantic model containing word n-grams vectors (or embeddings) which models semantic similarities between n-grams of different order. As data we use a large corpus of PubMed abstracts. The presented experiment is based on manual evaluation of extracted phrases for arbitrary queries provided by a group of evaluators. The results indicate that the proposed approach is promising and that the use of distributional semantic models trained with uni-, bi- and trigrams seems to work better than a more traditional unigram model.
Anthology ID:
W19-6114
Volume:
Proceedings of the 22nd Nordic Conference on Computational Linguistics
Month:
September–October
Year:
2019
Address:
Turku, Finland
Venues:
NoDaLiDa | WS
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Publisher:
Linköping University Electronic Press
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Pages:
131–139
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URL:
https://aclanthology.org/W19-6114
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Cite (ACL):
Hans Moen, Laura-Maria Peltonen, Henry Suhonen, Hanna-Maria Matinolli, Riitta Mieronkoski, Kirsi Telen, Kirsi Terho, Tapio Salakoski, and Sanna Salanterä. 2019. An Unsupervised Query Rewriting Approach Using N-gram Co-occurrence Statistics to Find Similar Phrases in Large Text Corpora. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 131–139, Turku, Finland. Linköping University Electronic Press.
Cite (Informal):
An Unsupervised Query Rewriting Approach Using N-gram Co-occurrence Statistics to Find Similar Phrases in Large Text Corpora (Moen et al., 2019)
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PDF:
https://aclanthology.org/W19-6114.pdf