Mining Web Usage Patterns for Online Recommendations
Web Usage Mining analyses the usage patterns of web sites in order to get an improved understanding of the users’ interests and requirements. This information is especially valuable for E-commerce sites in order to achieve improved customer satisfaction. Our approach is based on advanced data mining techniques to provide scalability and allow for flexible multidimensional data analysis. Furthermore, it can also be coupled with business warehouses for customer relationship management. One of the applications of our approach is for automatically determining online recommendations. Recommendations help users to quickly find the information they want or find interesting. On the other hand, they allow website owners to optimize the website, increase web user satisfaction and save on the costs of content management.
- Special Features and Advantages
Recommendations can be dynamically determined either based on manually specified rules or automatically determined by different recommendation algorithms.
Evaluates the effectiveness of recommendations using various data analytical tools.
Exploits user feedback to dynamically select the optimal recommendations.
Run-on Cloud and Big Data platform to effectively manage large amounts of usage data and support various recommender algorithms.
E-Business Provides ways to target the right customers and understand their needs and to customize services and strategies in near-or-real time.
Customer Relationship Management Converts web usage data into appropriate knowledge suitable to serve customers better, and improve the operations and accelerate the process of delivery of products to markets.
Advertisement Identifies potential prime advertisement locations