id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-020904-x3o3a45b	Montazeralghaem, Ali	Relevance Ranking Based on Query-Aware Context Analysis	2020-03-17		.txt	text/plain	5192	326	53	The primary goal of the proposed model is to combine the exact and semantic matching between query and document terms, which has been shown to produce effective performance in information retrieval. In basic retrieval models such as BM25 [30] and the language modeling framework [29] , the relevance score of a document is estimated based on explicit matching of query and document terms. Finally, our proposed model for relevance ranking provides the basis for natural integration of semantic term matching and local document context analysis into any retrieval model. [13] proposed a generalized estimate of document language models using a noisy channel, which captures semantic term similarities computed using word embeddings. Note that in this experiment, we only consider methods that select expansion terms based on word embeddings and not other information sources such as the top retrieved documents for each query (PRF).	./cache/cord-020904-x3o3a45b.txt	./txt/cord-020904-x3o3a45b.txt