How Will Science and Techonology Changes Our Lives in Future
Mining Web Transaction Patterns in Electronic Commerce Environment
With the popularity of the Internet and the development of e-commerce, the recommendation system has gradually become an important component of ecommerce IT technology, and has drawn the more and more attention from esearchers and business people. However, most of the existing e-commerce systems use only part of the information available to make recommendations. With the development of the research, the new e-commerce recommendation system should take advantage of as much information as possible, collect various types of data, efficiently integrate multiple recommend technologies in order to provide more effective recommendation services. At the same time, the expansion ability and the real-time requirement of the recommendation system are becoming more and more difficult to guarantee in a large-scale e-commerce recommendation system. So, the integration of multiple recommendation algorithms using various data and the real-time requirement are pressing problems in the development of e-commerce personalized service. In view of rich sources of e-commerce data, the key to problems can be nothing but the widespread application of the data mining technology and the establishment of a recommendation system model that can operate highly efficiently with multiple recommendation algorithms using various data.
4.2. System Architecture & Design
E-commerce personalized recommendation system and data mining Data mining is an uncommon process to extract the previously unknown and potentially useful information and knowledge from massive, incomplete, distributed, fuzzy and random data. This technology is widely used in classification, prediction and pattern recognition and so on. The biggest advantage of data mining technology for e-commerce is the massive data produced by the ecommerce conducts, which make just basis for data mining. At the same time, the e-commerce user
With the popularity of the Internet and the development of e-commerce, the recommendation system has gradually become an important component of ecommerce IT technology, and has drawn the more and more attention from esearchers and business people. However, most of the existing e-commerce systems use only part of the information available to make recommendations. With the development of the research, the new e-commerce recommendation system should take advantage of as much information as possible, collect various types of data, efficiently integrate multiple recommend technologies in order to provide more effective recommendation services. At the same time, the expansion ability and the real-time requirement of the recommendation system are becoming more and more difficult to guarantee in a large-scale e-commerce recommendation system. So, the integration of multiple recommendation algorithms using various data and the real-time requirement are pressing problems in the development of e-commerce personalized service. In view of rich sources of e-commerce data, the key to problems can be nothing but the widespread application of the data mining technology and the establishment of a recommendation system model that can operate highly efficiently with multiple recommendation algorithms using various data.
4.2. System Architecture & Design
E-commerce personalized recommendation system and data mining Data mining is an uncommon process to extract the previously unknown and potentially useful information and knowledge from massive, incomplete, distributed, fuzzy and random data. This technology is widely used in classification, prediction and pattern recognition and so on. The biggest advantage of data mining technology for e-commerce is the massive data produced by the ecommerce conducts, which make just basis for data mining. At the same time, the e-commerce user