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Multi-view Based Spatial-Keyword Query Processing for Real Estate

  • Xi Duan
  • Liping WangEmail author
  • Shiyu Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11642)

Abstract

The real estate search web systems such as Zillow, Anjuke, and Lianjia have become very popular in daily life. Generally, the comprehensive query results combined with transportation, health care, education, POIs, etc. are expected, but those surrounding information are rarely utilized in traditional query methods, which thereby restricts the results of the query. In this paper, we address the above limitations and provide a novel multi-view based query method, named KBHR. We investigate feature extraction method and introduce multi-view to represent comprehensive real estate data. The proposed method, KBHR, is based on BHR-tree which is a hybrid indexing structure and a kernel based similarity function developed to rank the query results of multi-view data. We construct experiments and evaluate KBHR on real-world data sets. The experimental results demonstrate the efficiency and effectiveness of our method.

Keywords

Spatial-keyword query Multi-view data Hybrid indexing structure Kernel function 

Notes

Acknowledgment

This work was partially supported by NSFC 61401155.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computer Science and Software EngineeringEast China Normal UniversityShanghaiChina

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