A trust and reputation model for filtering and classifying knowledge about urban growth

In this paper we present a trust and reputation model to classify and filter collaboratively contributed geographic information. We hypothesize that users contribute information in a collaborative system akin to Web 2.0 collaborative applications. We build on previous work where trust is proposed as a proxy for information quality and propose a spatial trust model to filter and extract high quality information about urban growth behaviors contributed by users. The motivating scenario involves residents of recently urbanized areas taking into account their interactions with their surroundings. The main contribution of this paper is a formal trust and reputation model that takes into account the spatial context of users and their contributions.