ON THE RELEVANCE OF QUERY EXPANSION USING PARALLEL CORPORA AND WORD EMBEDDINGS TO BOOST TEXT DOCUMENT RETRIEVAL PRECISION

Alaidine Ben Ayed1 And Ismaïl Biskri2
2020 Zenodo  
In this paper we implement a document retrieval system using the Lucene tool and we conduct some experiments in order to compare the efficiency of two different weighting schema: the well-known TF-IDF and the BM25. Then, we expand queries using a comparable corpus (wikipedia) and word embeddings. Obtained results show that the latter method (word embeddings) is a good way to achieve higher precision rates and retrieve more accurate documents
doi:10.5281/zenodo.3693272 fatcat:gm2qv3xozrcuxfnqxwwfgbl6cu