  Re-finding files from a personal computer is a frequent demand to users. When
encountered a difficult re-finding task, people may not recall the attributes
used by conventional re-finding methods, such as a file's path, file name,
keywords etc., the re-finding would fail.
  We proposed a method to support difficult re-finding tasks. By asking the
user a list of questions about the target, such as a document's pages, author
numbers, accumulated reading time, last reading location etc. Then use the
user's answers to filter out the target.
  After the user answered a list of questions about the target file, we
evaluate the user's familiar degree about the target file based on the answers.
We devise a ranking algorithm which sorts the candidates by comparing the
user's familiarity degree about the target and the candidates.
  We also propose a method to generate re-finding tasks artificially based on
the user's own document corpus.
