Query by Impression: A Novel Place Query System with Adjacency Constraints
Date Issued
2012
Date
2012
Author(s)
Lin, Shih-Han
Abstract
In our daily life, place query is one of the most fundamental applications.
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 the place. 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. For
example, a user may want to find a Japanese food restaurant which is located in the
eastern part of a city, and there are a park and a supermarket adjacent to this restaurant.
To enable the capability of query by impression that has not been fully explored in the
literature, in this paper, 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. Furthermore, we also consider using user query feedback to increase the
accuracy of the results. We implement a 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. Experiments with user study collected from 15
volunteers are conducted to validate the efficiency and effectiveness of the proposed
QBI system.
Subjects
Place Query
Location-based Service
Adjacency Constraints
Query By Impression
Type
thesis
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