Abstract:
The widespread availability and the technological advancements of geopositioning
devices enable users to generate a huge volume of geo-tagged objects
everyday. These objects include points of interest (e.g., restaurants), photos,
and buying/selling items. To describe such an object, which is commonly referred
as a spatial objet, users often use textual information 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
often issues a query like \ nd the Italian restaurant nearest to my location" to
a location based service provider (LSP), and the LSP returns the Italian hotel
that is nearest to the user’s location as an answer. Due to the popularity of
keyword search, this field leads much work on querying spatial keyword (SK)
search. However, there are many new applications which require incorporating
time along with location and textual information, e.g., \ nd the Italian
restaurant nearest to my location which opens at 10pm today". We term this
type of query as an spatio-temporal keyword (STK) query. A straightforward
way of answering STK queries using 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
organizes time along with location and keywords, and develop an
efficient algorithm for processing STK queries. We also extend our work to
handle time uncertainty. An extensive experimental study shows the efficiency
and effectiveness of our proposed techniques.
