User-based Filtering:
Take about 20-50 people who share similar taste with you, afterwards predict how much you might like an item depended on how much the others liked it.
Item-based Filtering:
Pick from your previous list 20-50 items that have similar people with “the target item”, how much you will like the target item depends on how much the others liked those earlier items.
Information needs of user and characteristics of items are represented in keywords, attributes, tags that describe past selections.An item is recommended to the user based on the scores calculated according to these preferences and characteristics.
Then comes the first question: What would happen if we mix them into one filter?
Undoubtedly the filtering may recommend a large range of products based on user's characteristic. In this case, the large range may not be our initial aim because user may lose their target again and ignore the filter.
Therefore we should choose one from the three types of Derived Social Recommendations according to what product we aim to recommend.
Second, I have a idea about Derived Social Recommendations that is background-based filtering.
Background-based Filtering
Background such as education level, hobby, age define a group of customers. The products they have bought create a sort of characteristic according to how much they may like the products.
This may be similar with the user-based filtering. But the key advantage of this filtering is that the defined characteristic keep changing according to the change of the whole background. I believe background-based filtering can match customer's demand best.
Hi,from your words, I can feel your carefulness about our course. I cann't agree more with your recognition about the two types of filtering, and also interest about your background filtering. People's cognitions would be infleunced by their backgrounds and also things aroud them.
回复删除Thank you for your comment! If you are interested in the background-based filtering, I am pleased to share more details with you.
删除Thank you for your elaborate analysis about our courses. And about your new idea, background-based filtering, I'm also interested in it. And I also think the personal background will influence a person's decision and favor. Of course, the background is such a large range. So maybe it's better that you can put more detailed lists that will affect personal ideas and analyze why and how they influence a person.
回复删除I actually haven't considered what background would brings with a large range of characteristic. Thanks for your comment which is so great, and I would think deeper in more detailed lists. Happy to learn from you.
删除I mean the background may be occuption, hometown, sex, age, education as you said, etc. And what decision these characters will bring? For example, majority of girls like going shopping and majority of boys like doing sports and playing computer games. The social networking's duty is to find how to automatically satisfy different users according to their distinctive background. Maybe at first, the users can write down their resumes before using the social networking product and the system can provide the match information to the users through their resumes.
删除Hahahahaha, this is a huge job!