Toward social search from explicit to implicit collaboration to predict users' interests

The concept of social search has been acquiring importance in the WWW as large-scale collaborative com-puting environments have become feasible.This field focuses on the reader's perspective in order to assign relevance and trustworthiness to web pages. Although current web searching technologies tend to rely on explicit human recommendations, these techniques are hard to scale as feedback is hard to obtain. Implicit feedback techniques, on the other hand, can collect data indirectly. The challenge is in producing implicit web-rankings by reasoning over users' activity during a web-search without recourse to explicit human inter?ventions. This paper presents a comparison between explicit and implicit users' feedbacks upon web pages. An experiment, involving 25 volunteers explicitly evaluating the usefulness of 12 thematic web-sites, was per?formed implicitly gathering their web browsing activity. The results obtained prove the existence of a strong correlation between explicit judgments and generated imlicit feedbacks.