Query by Impression: A Novel Place Query System with Adjacency Constraints

Place query is one of the most fundamental applications, and traditional use cases include finding the exact spatial location of a place and searching for a specific type of places in a given spatial range. On the other hand, there is another possibility that you may want to recommend a visited place to friends but forget the complete name of it. You have vague impressions on it and only remember the information of the place type, the rough range of the place, and some places near it. To enable the capability of query by impression that has not been fully explored in the literature, we define a new place query problem called Place Query with Adjacency Constraints (abbreviated as PQAC). We propose a naive approach and two enhancement algorithms, distance pre-calculating algorithm and grid indexing algorithm, to achieve greater efficiency that can satisfy the real-time need of this place query service. We implement the Query By Impression (abbreviated as QBI) system with a real metropolitan place dataset consisting of more than 40,000 place records from Google Place API. Several experiments are conducted to validate the efficiency and effectiveness of the proposed QBI system.