Community-aware Recipe Profiling for Personalized Search in Folksonomy
Project: Research
Description
In recent years, there is a fast proliferation of collaborative tagging (a.k.a. folksonomy) systems in Web 2.0 communities. With the increasingly large amount of recipe data, how to assist user in searching their interested recipes by utilizing these semantic tags becomes an interesting problem. Collaborative tagging systems provide an environment for users to annotate recipes. However, users may have different perspectives or feelings on recipes, e.g., some of them may share similar perspectives yet have a conflict with others. Thus, modeling the profile of a recipe based on tags given by all users who have annotated the recipe is neither suitable nor reasonable. To tackle this problem, we propose a community-aware approach to constructing recipe profiles via social filtering. In order to discover user communities, three different strategies are to be devised. Moreover, we propose a personalized search approach to optimize personalized recipe ranking based on user preferences and user issued query. We will conduct experiments on a collected real life data set by comparing the performance of our proposed approach and baseline methods.Detail(s)
Project number | 7002770 |
---|---|
Grant type | SRG |
Status | Finished |
Effective start/end date | 1/05/12 → 29/05/14 |