Efficient retrieval of the top-k most relevant spatial web objects
Proceedings of the VLDB Endowment
Retrieving top-k prestige-based relevant spatial web objects
Proceedings of the VLDB Endowment
Mining significant semantic locations from GPS data
Proceedings of the VLDB Endowment
Reverse spatial and textual k nearest neighbor search
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Collective spatial keyword querying
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Efficient continuously moving top-k spatial keyword query processing
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
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Spatial-textual content is becoming increasingly prevalent: — Location-based services from major commercial search engines. For example, in Google Maps many (geo-referenced) points of interest--e.g., clinics, stores, tourist attractions, hotels, entertainment services, public transport, and public services--are being associated with descriptive texts. — Websites with location content. For example, online yellow pages, documents of Wikipedia, Tweets in Twitter, photos in Flickr, points of interest in Foursquare, etc. — Moving objects associated with texts. An example scenario is that each healthcare worker has certain skills, described in keywords, and moves around in a large hospital. These call for spatial-keyword search from the perspectives of both the users and the service providers. From the user's perspective, users may want to issue queries such as "health screening clinics near NTU, Singapore", which has a location component "NTU, Singapore" and a keyword component "health screening clinics". Indeed, location-based services (e.g., Google Maps) and Twitter already support such types of queries. From the perspective of service providers, they want to know the number of customers who are interested in their services compared with competitors. For example, a nutrition store may want to find potential customers whose profiles are relevant to the products of the store and whose locations are close to this store. The talk covers recent results [1---6] on spatial keyword querying obtained by the speaker and his colleagues.