Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Capturing knowledge of user preferences: ontologies in recommender systems
Proceedings of the 1st international conference on Knowledge capture
Programming and Deploying Java Mobile Agents Aglets
Programming and Deploying Java Mobile Agents Aglets
Toward an Open Virtual Market Place for Mobile Agents
WETICE '99 Proceedings of the 8th Workshop on Enabling Technologies on Infrastructure for Collaborative Enterprises
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With the rapid development of Internet technologies, theInternet makes infinite charms and enormous populationand also makes E-Commerce well developed. Mobileagents are mobile, personalized, autonomous, andadaptive. These qualities make mobile agents useful for theinformation-rich and communication-rich environmentsuch as E-Commerce. The common online shoppingmarkets commerce sites have two kinds of main drawbacks:1.Because of the different product data format in databaseand representation, it is difficult to exchange informationbetween the two online markets. 2.Consumers must searchand filter product information by browsing a lot ofshopping sites and have to compare the product prices bythemselves. 3.It's hard to accumulate consumer's loyalty.Therefore, the purpose of the paper is to extend the Ecommerceplatform that developed by our agent-based ECommerceresearch group and build an agent-batedconsumer recommendation mechanism. Followed themechanism, agents on behalf of consumer can trade in theE-commerce platform and record the consumer preferenceand produce the appropriate product recommendinformation according to consumer's preference.