2017
DOI: 10.1007/s10489-017-0977-1
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Graph bandit for diverse user coverage in online recommendation

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Cited by 12 publications
(8 citation statements)
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“…As an important research content in the cross-border e-commerce enterprise, the association rule has been promoted in various industries, and it has quickly become a very popular research field, where the more typical algorithms are Apriori and FP-growth [26]. In the era of big data, the boundaries between data attribute values cannot be strictly divided.…”
Section: Association Rulementioning
confidence: 99%
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“…As an important research content in the cross-border e-commerce enterprise, the association rule has been promoted in various industries, and it has quickly become a very popular research field, where the more typical algorithms are Apriori and FP-growth [26]. In the era of big data, the boundaries between data attribute values cannot be strictly divided.…”
Section: Association Rulementioning
confidence: 99%
“…e distributed system can provide large-scale data storage system, and the distributed batch processing framework Map-Reduce can provide a distributed application development interface. So the distributed computing platform can effectively improve the efficiency of our proposed algorithm, make full use of the Mathematical Problems in Engineering computing power of all servers, and enhance the scalability of our proposed algorithm [26,[28][29][30].…”
Section: Design and Implementation Of Our Proposed Recommendation Systemmentioning
confidence: 99%
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“…Recommendations from the perspective of coverage are mostly item-oriented and typically, not adopting socio-awareness. In [91,92], the problem of recommendations is related to the Maximum Coverage Problem. In [91], users are distinguished to different types according to their preferences to items, where preferences can vary over time.…”
Section: Efficient Socio-aware Recommendations Under Complex User Constraintsmentioning
confidence: 99%