Designing an Agent for Information Extraction from Persian E-shops
Nasrin Rasouli, Leila Abedi, Sara Ghaei
E-shops are among the most conventional applications of Electronic Commerce. In these shops, the buyers search for their goods through key words or classifications and read the product description provided by the sellers. Though, when the number of items is high, this gets to be difficult for the users. On the one hand, there are too many e-shops, and browsing in these shops to find the best and most appropriate goods is a difficult and time-consuming process. On the other hand, product descriptions are not the same in different websites, and there are different product forms. This study investigates about products and sellers in various websites based on the conditions and user requirements through software agents which present the extracted information in the form of a table to the users which enables them to compare prices and each seller’s conditions without spending too much time for browsing. Using this method increases precision and recall indices comparing to a conventional user browsing.
e-shops; intelligent agents; information extraction; persian language; ontology