【2010'COLING】FactRank: RandomWalks on a Web of Facts

这篇文章的motivation是when two fact instances from two relations share the same value for a shared argument type, then the validity of both facts should be increased. Conversely, we also hypothesize that an incorrect fact instance will
tend to match a shared argument with other facts far less frequently.

他下面举了一个例子：

t1: acted-in<Psycho, Anthony Perkins>

t2: *acted-in<Walt Disney Pictures, Johnny Depp>

t3: director-of<Psycho, Alfred Hitchcock>

t4: is-actor<Anthony Perkins>

因为t3中提到Psycho是电影，所以t1的证据被加强了，同时t4提到Anthony Perkins是一个演员，因此t1的证据也被加强了，另一方面，t1也加强了t3和t4的证据。相比之下t2是错误的，所以提到的fact就要少了。所以这个过程可以由Random Walk进行建模。真是一个好idea！！

后面的方法就是改改PageRank，实验只做了Movie领域的，感觉有点少，但是idea不错