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With the continuous development of real estate and the increasing personalization of people, more and more homeowners are willing to search for and discover their preferred decorative art patterns via various house decoration websites or platforms. Through browsing and analyzing existing house decoration cases on the web, a new homeowner can find his or her 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 homeowners clustering approach is proposed. A set of experiments are designed to validate the effectiveness and efficiency of the proposal.

Decorative Art Pattern Mining and Discovery Based on Group User Intelligence