Clustering-based Semantic Retrieval Algorithm
Xiang Helin, Mingxi Zhang, Pohan Li, Zhenying He, Wei Wang · Jisuanji gongcheng · 2012
(Abstract )Latent Semantic Analysis(LSA) lacks computation efficiency and has storage deficiencies when it is used in the large scale semantic retrieval. To solve this problem, this paper proposes a clustering-based semantic retrieval algorithm. This algorithm clusters the documents using their structural information, and applies the LSA process on those clusters to efficiently reduce the number of documents. Experimental results show that the algorithm can exponentially decrease the time of inquiring and get good retrieval accuracy.