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Abstract
The widespread availability and the technological advancement of geo-positioning devices enable users to generate a high volume of geo-tagged objects everyday. These objects include points of interests, photos, and buying/selling items. To describe such an object, which is commonly referred as a spatial object, users often use textual description or keywords along with the geographic location of the entity. Based on these geo-tagged objects, a large variety of location-based services has been emerged. For example, a user may want to find an Italian restaurant nearest to his location. We envision a new set of applications that require incorporating time along with location and textual information, e.g. find the Italian restaurant nearest to my location, which opens at 10 pm today. We term this type of query as a spatio-temporal keyword (STK) query. A straightforward way of answering STK queries using an existing spatial keyword search technique requires retrieving objects that are not temporally relevant to the query time. To solve this issue, in this paper, we introduce a new index structure that hierarchically organises time along with location and keywords, and develop an efficient algorithm for processing STK queries. We also extend our work to handle time uncertainty in STK queries. An extensive experimental study shows the efficiency and effectiveness of our proposed techniques.
Notes
No potential conflict of interest was reported by the authors.
1 We have used two names -tree and
-tree interchangeably throughout this paper.