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We are interested in combining 2 recommendation techniques, the computation of prediction score is established in step 1.3.3:
p_(u,i)= 𝛼_𝑢∗p_(u,i)^CF+(1−𝛼_𝑢 )∗p_(u,i)^CBF
Different from some related works, our contribution is that we form a simple calculation for 𝛼 with respect to a confidence factor. 𝛼 will be given in step 1.2:
𝛼_𝑢=𝑡_𝑢/𝑘∗0.9
, where k: number of neighbours used for ranking k ∈ℕ, and 𝑡_𝑢 is the number of items ∈ I\𝐈_𝐮. Note that, in case that 𝑡_𝑢 is greater than k, set〖 𝑡〗_𝑢= k. We called the ratio between 𝑡_𝑢 and b as a confidence factor for each user u.
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IEEE/ICACT20200192 Slide.11
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