Direction-based surrounder queries for mobile recommendations

  • Authors:

  • Xi Guo;Baihua Zheng;Yoshiharu Ishikawa;Yunjun Gao

  • Affiliations:

  • Graduate School of Information Science, Nagoya University, Nagoya, Japan 464-8601;School of Information Systems, Singapore Management University, Singapore, Singapore 178902;Graduate School of Information Science, Nagoya University, Nagoya, Japan 464-8601;College of Computer Science, Zhejiang University, Hangzhou, People's Republic of China 310027

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 2011

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Abstract

Location-based recommendation services recommend objects to the user based on the user's preferences. In general, the nearest objects are good choices considering their spatial proximity to the user. However, not only the distance of an object to the user but also their directional relationship are important. Motivated by these, we propose a new spatial query, namely a direction-based surrounder (DBS) query, which retrieves the nearest objects around the user from different directions. We define the DBS query not only in a two-dimensional Euclidean space $${\mathbb{E}}$$ but also in a road network $${\mathbb{R}}$$ . In the Euclidean space $${\mathbb{E}}$$ , we consider two objects a and b are directional close w.r.t. a query point q iff the included angle $${\angle aqb}$$ is bounded by a threshold specified by the user at the query time. In a road network $${\mathbb{R}}$$ , we consider two objects a and b are directional close iff their shortest paths to q overlap. We say object a dominates object b iff they are directional close and meanwhile a is closer to q than b. All the objects that are not dominated by others based on the above dominance relationship constitute direction-based surrounders (DBSs). In this paper, we formalize the DBS query, study it in both the snapshot and continuous settings, and conduct extensive experiments with both real and synthetic datasets to evaluate our proposed algorithms. The experimental results demonstrate that the proposed algorithms can answer DBS queries efficiently.