I want to solve this data mining problem:

  1. There is a sequence $S(t) = [A_1,...,A_{t-1}]$ .
  2. Each $A_i \subset U$ are set.
  3. Current time is $t \in \mathbb{N}$.
  4. $B$ is a subset of $A_t$. ($B \subset A_t$)
  5. $U$ is possible choices of a player.
  6. $I(S(t)) = \{1,...,t-1\}$ is indices of the sets in sequence.
  7. We can use $B$, $S(t)$ and $I(S(t)) \cup \{t\}$ to predict it .
  8. We already know $A_1,...,A_{t-1},B $ but we don't know $A_t-B$.
  9. Each element $x \in A_i$ only have ID of element. i.e. $x \in \mathbb{N}$.
  10. Objective is to predict $A_t - B$.

For example, a user can input tags as $A_i$ like $A_i =\{software, python \}$ and we call it "post". He already posted $A_1,...,A_{t-1}$ and inputted $B$. We want to predict tags on current post $t$.

Or another example is book-recommendation. A user bought books like $A_i = \{bookA, bookB\}$ and $i$ is a time. If he already selects some books on current time $t$, it means $|B|>0$, and the purpose is to recommend $A_t-B$.

I've tried to build a co-occurrence graph with frequency weight, but its accuracy was not so good.

Could you tell me how to solve it?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.