Ranking friends' posts on Facebook using hypernyms and tf-idf based on cosine similarity
○陳 思婉(立命館大),Chengguang SHEN(大連理工大),西出 亮,Ian PIUMARTA,高田秀志(立命館大)
People now spend more time on social media than other internet activities. On Facebook, however, it is possible to miss posts from friends who have similar interests but who are only weakly associated with the user, since Facebook ranks posts based on affinity and type of post but rarely inspect the contents of the posts. We are therefore trying to discover friends with similar interests and recommend their posts to the user. To calculate similarities we use tf-idf and cosine similarity to measure how closely related one document is to others in a collection. We combine that with hypernyms to extract the generic meanings of words, which yields a better similarity metric. Using this approach we can connect Facebook users with weakly-associated friends whose posts are demonstrating similar interests.

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