Base-package recommendation framework based on consumer behaviours in IPTV platform

• Main Authors: SHANMUGALINGAM, Kuruparan, RANGANAYANKE, Ruwinda, GUNAWARDHAHA, Chanka, NAVARATHNA, Rajitha
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Customer scoring; Feature engineering; Machine learning; Recommendation system; Clustering; Collaborative filtering; Content filtering; Customer Churn; Numerical Analysis and Scientific Computing; Television; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/5917; https://ink.library.smu.edu.sg/context/sis_research/article/6920/viewcontent/Base_Package_IPTV_2020.pdf
• Institution: Singapore Management University

Internet Protocol TeleVision (IPTV) provides many services such as live television streaming, time-shifted media, and Video On Demand (VOD). However, many customers do not engage properly with their subscribed packages due to a lack of knowledge and poor guidance. Many customers fail to identify the...