Information that finds the User; Recommender Systems and Semantic Web.
In response to the increasing flood of information on the web, new ways are being sought to more efficiently evaluate and sort information.
Following the processes of information retrieval and data processing, Astina can individually filter out user-relevant information through a recommender system. This ensures that only information applicable to the user will be found in the search.
The information is consolidated, enriched with meta-information and finally tailored to each users individual preferences. The system learns from personal user behaviour and preferences and compares these to similar user behaviour models in order to calculate an exact individual user recommendation.
Customised user recommendation systems are useful for a wide range of applications, for example job or real estate advertisements, financial information, classifieds, address information, news articles, event information or social networks. As the number of users increases, the recommendations not only become more accurate, but also generate a statistical basis for strategic decisions and opportunities for cross-selling and strategic development.