We are focusing on the studies of the spatial-temporal search & mining.
This site publishes interesting demos built on top of the technology studied in our research.
With the increasing popularity of mobile devices and location based services, massive amount of geo-textual data (e.g., geo-tagged tweets) is being generated everyday. Compared with traditional spatial data, the textual dimension of geo-textual data greatly enriches the data. Meanwhile, the spatial dimension of geo-textual data also adds a semantically rich new aspect to textual data. The large volume, together with its rich semantics, calls for the need for data exploration. First, it has many applications to retrieve a region for exploration that satisfies user-specified conditions (e.g., the size and shape of the region) while maximizing some other conditions (e.g., the relevance to the query keywords of the objects in the region). Second, it is useful to mine and explore the topics of the geo-textual data within a (specified or retrieved) region and perhaps a timespan. This demonstration proposal presents the main ideas of our system, the Region Search and Exploration System (RSE), for efficiently supporting region search and exploration, and our demonstration plan.
Rich geo-textual data is available online and the data keeps in- creasing at a high speed. We propose two user behavior models to learn several types of user preferences from geo-textual data, and a prototype system on top of the user behavior models for querying and mining geo-textual data to support personalized maps. Dif- ferent from existing recommender systems and data analysis systems, our system highly personalizes user experience on maps and supports several applications, including user mobility & interests mining, opinion mining in regions, user recommendation, point-of-interest recommendation, and querying and subscribing on geo- textual data.