Abstract
Finding matching customers for a product is critical in many applications, especially in the e-commerce field. In this paper, we propose a novel product-customer matching framework to handle this issue, which consists of two components: data preprocessing and query processing. During the data preprocessing phase, a generation rule is proposed to learn the user’s preference. With the spread of the web 2.0 applications, users like to rate some products they have experienced in the social applications, e.g. Dianping and Yelp. Hence, it is possible to construct users’ preferences based on their rating information. In the query processing phase, we first propose Top-k-Ranks Query, which integrates reverse top-k query and reverse k-ranks query, to find some users to match the query product, and then devise an efficient method (BBPA) to handle this new query. Finally, we evaluate the efficiency and effectiveness of our matching framework upon real and synthetic datasets, showing that our framework works well in finding matching users for a query product.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chang, Y.-C., Bergman, L.D., Castelli, V., Li, C.-S., Lo, M.-L., Smith, J.R.: The onion technique: Indexing for linear optimization queries. In: Proc. of ACM SIGMOD, pp. 391–402 (2000)
Chester, S., Thomo, A., Venkatesh, S., Whitesides, S.: Indexing reverse top-k queries. CoRR abs/1205.0837 (2012)
Hristidis, V., Koudas, N., Papakonstantinou, Y.: Prefer: A system for the efficient execution of multi-parametric ranked queries. In: Proc. of ACM SIGMOD, pp. 259–270 (2001)
Ge, S., Leong Hou, U., Mamoulis, N., Cheung, D.: Efficient all top-k computation - a unified solution for all top-k, reverse top-k and top-m influential queries. IEEE Trans. Knowl. Data Eng. 25(5), 1015–1027 (2012)
Vlachou, A., Doulkeridis, C., Kotidis, Y., Nørvåg, K.: Reverse top-k queries. In: Proc. of ICDE, pp. 365–376 (2010)
Zhang, Z., Jin, C., Kang, Q.: Reverse k-ranks query. PVLDB 7(10), 785–796 (2014)
Vlachou, A., Doulkeridis, C., Nørvåg, K., Kotidis, Y.: Branch-and-bound algorithm for reverse top-k queries. In: SIGMOD Conference, pp. 481–492 (2013)
B\(\ddot{o}\)rzs\(\ddot{o}\)nyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proc. of ICDE, pp. 421–430 (2001)
Vlachou, A., Doulkeridis, C., Kotidis, Y., Nørvåg, K.: Monochromatic and bichromatic reverse top-k queries. IEEE Trans. Knowl. Data Eng. 23(8), 1215–1229 (2011)
Shani, G., Gunawardana, A.: Evaluating recommendation systems. In: Recommender Systems Handbook, pp. 257–297. Springer (2011)
Adomavicius, G., Zhang, J.: On the stability of recommendation algorithms. In: Proceedings of the Fourth ACM Conference on Recommender Systems, pp. 47–54. ACM, New York (2010)
Yin, H., Sun, Y., Cui, B., Hu, Z., Chen, L.: Lcars: a location-content-aware recommender system. In: KDD, pp. 221–229 (2013)
Xu, C., Zhou, M., Chen, F., Zhou, A.: Detecting user preference on microblog. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds.) DASFAA 2013, Part II. LNCS, vol. 7826, pp. 219–227. Springer, Heidelberg (2013)
Gerogiannis, V.C., Karageorgos, A., Liu, L., Tjortjis, C.: Personalised fuzzy recommendation for high involvement products. In: SMC, pp. 4884–4890 (2013)
Li, C.: Enabling data retrieval: by ranking and beyond. PhD thesis, University of Illinois at Urbana-Champaign (2007)
Lian, X., Chen, L.: Probabilistic inverse ranking queries in uncertain databases. VLDB J. 20(1), 107–127 (2011)
Lee, K.C.K., Ye, M., Lee, W.C.: Reverse ranking query over imprecise spatial data. In: COM. Geo. 17:1–17:8 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Kang, Q., Zhang, Z., Jin, C., Zhou, A. (2014). A Product-Customer Matching Framework for Web 2.0 Applications. In: Benatallah, B., Bestavros, A., Manolopoulos, Y., Vakali, A., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2014. WISE 2014. Lecture Notes in Computer Science, vol 8787. Springer, Cham. https://doi.org/10.1007/978-3-319-11746-1_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-11746-1_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11745-4
Online ISBN: 978-3-319-11746-1
eBook Packages: Computer ScienceComputer Science (R0)