  Re-finding electronic documents from a personal computer is a frequent demand
to users. In a simple re-finding task, people can use many methods to retrieve
a document, such as navigating directly to the document's folder, searching
with a desktop search engine, or checking the Recent Files List. However, when
encountering a difficult re-finding task, people usually cannot remember the
attributes used by conventional re-finding methods, such as file path, file
name, keywords etc., the re-finding would fail. We propose a new method to
support difficult re-finding tasks. When a user is reading a document, we
collect all kinds of possible memory pieces of the user about the document,
such as number of pages, number of images, number of math formulas, cumulative
reading time, reading frequency, printing experiences etc. If the user wants to
re-find a document later, we use these collected attributes to filter out the
target document. To alleviate the user's cognitive burden, we use a question
and answer wizard interface and provide recommendations to the answers for the
user, the recommendations are generated by analyzing the collected attributes
of each document and the user's experiences about them.
