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.
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References
Hartz, D.K., Gorman, M.T., Rossum, E.: Real-estate information search and retrieval system. In: US (2003)
Martinez, L., Contreras, J., Mendoza, R.: INMO: a web architecture for real estate search systems. IEEE Latin Am. Trans. 13(4), 1148–1152 (2015)
Liu, X.P., Wan, C.X., Liu, D.X.: Survey on spatial keyword search. J. Softw. 27(2), 329–347 (2016)
Chen, L., Cong, G., Jensen, C.S.: Spatial keyword query processing: an experimental evaluation. Proc. VLDB Endow. 6(3), 217–228 (2013)
Cao, X., Cong, G., Jensen, C. S., Ooi, B.C.: Collective spatial keyword querying. In: SIGMOD Conference, pp. 373–384 (2011)
Chen, L., Cong, G., Cao, X.: An efficient query indexing mechanism for filtering geo-textual data. In: SIGMOD Conference, pp. 749–760 (2013)
Wu, D., Yiu, M.L., Cong, G., Jensen, C.S.: Joint top-k spatial keyword query processing. IEEE Trans. Knowl. Data Eng. 24(10), 1889–1903 (2012)
Zhang, C., Zhang, Y., Zhang, W.: Inverted linear quadtree: efficient top k spatial keyword search. IEEE Trans. Knowl. Data Eng. 28(7), 1706–1721 (2016)
Zhou, Y., Xie, X., Wang, C.: Hybrid index structures for location-based web search. In: International Conference on Information & Knowledge Management, pp. 155–162. ACM (2005)
Felipe, I.D., Hristidis, V., Rishe, N.: Keyword search on spatial databases. In: IEEE International Conference on Data Engineering, pp. 656–665 (2008)
Xu, C., Tao, D., Xu, C.: A survey on multi-view learning. Comput. Sci. (2013)
Eaton, E., Desjardins, M., Jacob, S.: Multi-view clustering with constraint propagation for learning with an incomplete mapping between views. In: ACM International Conference on Information & Knowledge Management, pp. 389–398 (2010)
Deng, C., Lv, Z., Liu, W.: Multi-view matrix decomposition: a new scheme for exploring discriminative information. In: International Conference on Artificial Intelligence, pp. 3438–3444. AAAI Press (2015)
Yuan, N.J., Zheng, Y., Xie, X.: Discovering urban functional zones using latent activity trajectories. IEEE Trans. Knowl. Data Eng. 27(3), 712–725 (2015)
Zheng, Y., Liu, F., Hsieh, H.P.: U-Air: when urban air quality inference meets big data. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1436–1444 (2013)
Wang, Y., Cheema, M.A., Lin, X., Zhang, Q.: Multi-manifold ranking: using multiple features for better image retrieval. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds.) PAKDD 2013. LNCS (LNAI), vol. 7819, pp. 449–460. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37456-2_38
Dhillon, P.S., Foster, D., Ungar, L.: Multi-view learning of word embeddings via CCA. In: Proceedings of Nips, pp. 199–207 (2011)
Krainer, J., Wei, C.: House prices and fundamental value. FRBSF Econ. Lett. (2004)
Kamel, I., Faloutsos, C.: Hilbert R-tree: an improved R-tree using fractals. In: International Conference on Very Large Data Bases, pp. 500–509 (1994)
Manning, C., Raghavan, P.: Introduction to Information Retrieval, pp. 824–825. Cambridge University Press, Cambridge (2010)
Yu, L.H., Du, Y.: Methods and technology of data preprocess in data mining. J. Anhui Vocat. College Electron. Inf. Technol. (2009)
Fu, K.S.: Pattern Recognition and Machine Learning, pp. 461–462. Springer, New York (2006)
Liu, L.: Normalized discounted cumulated gain (nDCG). Encyclopedia of Database Systems, p. 1920. Springer, Boston (2009). https://doi.org/10.1007/978-0-387-39940-9_3166
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This work was partially supported by NSFC 61401155.
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Duan, X., Wang, L., Yang, S. (2019). Multi-view Based Spatial-Keyword Query Processing for Real Estate. In: Shao, J., Yiu, M., Toyoda, M., Zhang, D., Wang, W., Cui, B. (eds) Web and Big Data. APWeb-WAIM 2019. Lecture Notes in Computer Science(), vol 11642. Springer, Cham. https://doi.org/10.1007/978-3-030-26075-0_22
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