|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|152549||2018||16 صفحه PDF||سفارش دهید||11195 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Approximate Reasoning, Volume 95, April 2018, Pages 77-92
High Utility Sequential Patterns (HUSP) are a type of patterns that can be found in data collected in many domains such as business, marketing and retail. Two critical topics related to HUSP are: HUSP mining (HUSPM) and HUSP Hiding (HUSPH). HUSPM algorithms are designed to discover all sequential patterns that have a utility greater than or equal to a minimum utility threshold in a sequence database. HUSPH algorithms, by contrast, conceal all HUSP so that competitors cannot find them in shared databases. This paper focuses on HUSPH. It proposes an algorithm named HUS-Hiding to efficiently hide all HUSP. An extensive experimental evaluation is conducted on six real-life datasets to evaluate the performance of the proposed algorithm. According to the experimental results, the designed algorithm is more effective than three state-of-the-art algorithms in terms of runtime, memory usage and hiding accuracy.