A Modified Weight Function in Latent Semantic Analysis
Yunfeng Liu · Zhongwen xinxi xuebao · 2005
Since the first paper about Latent Semantic Analysis(LSA) was published,LSA has been applied to many fields,such as information retrieval,text classification,automatic question answering,etc..One important factor that affects the quality of LSA is the weighting scheme to the term-document matrix.In this paper,we first summarize the traditional and well-studied methods of weighting,including local weighting and global weighting.We then point out some inadequacy of original methods,modify these methods,and present the concept of global weighting of document.In the last part of this paper,we construct an experiment to compare the results of LSA with different types of weighting,in which we present a new measure to evaluate the result of LSA.We call this new measure self-indexing matrix.The result of the experiment confirms that the modified method of weighting can improve the efficiency of retrieval.