PersonalizedWeb Advertising Method..

TL;DR: The multi-agent system running mostly on the publisher site is introduced to organize personalized advertising to provide advertisements, which are most suitable for the given anonymous user navigating the web site.

TL;DR: This work presents a general overview of the AdMotional system architecture, and introduces the learning and optimization component and strategies before concluding with a summary and brief outlook into future developments.

TL;DR: Positive and confined negative association rules are the components of the new quality measures: Positive and Negative Quality function, respectively, used to evaluate the quality of hyperlinks existing on web pages.

TL;DR: A generalised model, the Layered Adaptive Advertising Integration (LAAI), is proposed as the starting point for the development of an adaptive advertisement system and social interactions are added to the user model, and the delivery process has the ability to apply actions based on this data.

TL;DR: A state-of-the-art taxonomy of intelligent recommender agents on the Internet and a cross-dimensional analysis with the aim of providing a starting point for researchers to construct their own recommender system.

TL;DR: Visualize data sets and clustering results by Principal Component Analysis (PCA), which can be implemented yourself or use any existing implementation or package.

TL;DR: A Web ad selector is proposed that personalizes advertising messages for customers based on their preferences and interests and uses fuzzy rules that express customer segments' surfing patterns on the basis of expert advice, and recommends appropriate ads by fuzzy inference.

TL;DR: A framework and overview of general methods for optimizing the management of advertisements on web servers are discussed and a number of statistical, optimization and scheduling models are provided.