Transcript from the "Chatbot Recommendations" Lesson
>> Bianca Gandolfo: We created our data structure. We have an ability to insert nodes, build our tree, build up our recommendations and questions, right? Maybe, we could get there.
>> Bianca Gandolfo: No, still confused?
>> Bianca Gandolfo: All right, we'll keep going, unless you stop me, all right. So we have our data structure, we need to do something useful with it, right?
[00:00:33] So we built it, now let's run an algorithm on it. Seems reasonable, seems like the logical next step. We have the thing, now let's do something with it. So I think a good starting point for this is just to count the number of recommendations that our chat-bot can recommend.
[00:00:54] How might we differentiate a recommendation from a question?
>> Speaker 2: It wouldn't have any children.
>> Bianca Gandolfo: Yeah, yeah, so if we get to a node that doesn't have any children, that can be a recommendation. So just like we had to go down a path, we have our recommendation. Any other ways that we can do it?
>> Speaker 3: Depends on the tree, right? Cuz if it's binary, then you could just assume that it's only two, right or no?
>> Bianca Gandolfo: Well, so our recommendation is binary, actually cuz we have yes and no. So each question will only have two options, yes and no.
>> Speaker 3: So each node would be the same, you could extrapolate then from the nodes the recommendation, the number of recommendations?
>> Bianca Gandolfo: But how?
>> Speaker 3: You can look for the yes or no keys in the object.
>> Bianca Gandolfo: So maybe if it's a recommendation we don't have a yes or no option?
>> Speaker 3: Yes.
>> Bianca Gandolfo: Cool, cool, all reasonable.
>> Bianca Gandolfo: So here's our tree, we have our questions and then we have our recommendations, so,
>> Bianca Gandolfo: This looks familiar, right? So if you were to adapt your tree with insert child, what would be the different?
>> Bianca Gandolfo: You guys just did the exercise, what are the different about building this? All right, let's take a look.