id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_zdavkplsyndrvpy6xenfzuotre	Qiming Luo	A semantic term weighting scheme for text categorization	2011	19	.pdf	application/pdf	6279	639	61	proposed weighting scheme makes use of the concept associations to build document vectors for clustering. Keywords: Neural networks, Concept embedding, Biomedical text clustering and In this research, we propose and evaluate a framework for biomedical text clustering and visualization based on the concept embedding of diseases. based on the concept embedding for biomedical text document representation, clustering, and visualization. In order to properly make use of the concept embedding for text clustering and visualization, in this research, a new weighting scheme is proposed ( W(Ci, d) ) to calculate Figures 5, 6, and 7 show the returned values of the DBindex for baseline tf–idf, proposed weighting scheme based on aggregated word embedding and intact concept The returned DBindex values show that the proposed weighting scheme based on aggregated word embedding works better than the Concept embedding-based weighting scheme for biomedical text clustering and visualization Concept embedding-based weighting scheme for biomedical text clustering and visualization	./cache/work_zdavkplsyndrvpy6xenfzuotre.pdf	./txt/work_zdavkplsyndrvpy6xenfzuotre.txt