Decorative Art Pattern Mining and Discovery Based on Group User Intelligence

Abstract

With the continuous developments of real estates and the increasing personalization of people, more and more house owners are willing to search for and discover their preferred decorative art patterns via various house decoration cases sharing websites or platforms. Through browsing and analyzing existing house decoration cases on the Web, a new house owner can find out his or her interested decorative art patterns; however, the above decorative art pattern mining and discovery process is often time-consuming and boring due to the big volume of existing house decoration cases on the Web. Therefore, it is becoming a challenging task to develop a time-efficient decorative art pattern mining and discovery method based on the available house decoration cases provided by historical users. Considering this challenge, a novel LSH-based similar house owners clustering approach is proposed. A set of experiments are designed to validate the effectiveness and efficiency of our proposal.

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