A peer to peer housing rental system with continuous spatial-keyword searching

Abstract

Apart from traditional intermediary companies, online housing rental systems as their convenience are gaining their popularity. Search is a critical function in these systems, but it does not always meet users’ satisfaction. For example, spatial and keyword distributions are generally be considered separately and the user cannot submit a continuous query requirement before he/she rent a satisfied house. In this paper, we develop a peer to peer housing rental system (P2PHRS) based on Django Framework of Python. We propose an efficient house searching algorithm called Quad-tree plus Inverted List (QIL) to filter housing resources for users according to their spatial and keyword requirements. P2PHRS is designed to be adaptive to a variety of front-end clients, like Web, Android and iOS platform etc.We show the advantages of P2PHRS by several spatial-keyword query demonstration scenarios.