CusFinder: An Interactive Customer Ranking Query System

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Authors: Xiaojun Xie, Xiaolin Qin, Xingluo Li, Yanghao Zhou

Tags: 2018, conceptual modeling

Finding a certain number of objects with optimum ranking based on spatial position constraints and given preference of attributes can be essential in numerous scenarios. In this paper, we demonstrate CusFinder, an interactive customer ranking query system to retrieve customers who favour a specific seller more than other people from the perspective of sellers, instead of retrieving sellers for a given customer similar to existing commercial systems. To make the query processing more efficient, a novel indexing is proposed to serve for query engine. Furthermore, we present the result of queries upon multiple visualization views with user-friendly interaction designs.

Read the full paper here: https://link-springer-com.proxy2.hec.ca/chapter/10.1007/978-3-030-01391-2_13