Publication at Faculty of Mathematics and Physics |
2009
Abstract
We present models, methods, implementation and experiments with a system enabling personalized web search for many users with different preferences. System consists of a web information extraction part, text search engine, middleware supporting top-k answers and a user interface for querying and evaluation and learning of satisfaction with search results.
We integrate several tools (implementing our models and methods) into one framework connecting user with the web. The model is based on modeling preferences by fuzzy sets and fuzzy logic here understood as scoring describing user preference and satisfaction.
Our model was experimentally implemented and the integration was tested.