Latent Semantic Information Extraction and Classification of Online Product
Jiang Jian-hon · Computer and Digital Engineering · 2014
In web-based e-commerce data mining process,how to discover the useful information from a large number of commodity trading records is the main subject of current research.Through analyzing the characteristics of online trade product name information,a custom web page crawler is used to gather online commodity trading information,then word segmentation is used to process the product names data,at last latent semantic analysis is made to analyze the type of data set and achieve a product category classification algorithm.From the division results,the algorithm can remove redundant information,effectively distinguish different categories of goods.