A user initially judges whether each of pieces of information input as learning
information is necessary or unnecessary, matrix elements of an affirmative metric
signal indicating the records of the necessary information and matrix elements
of a negative metric signal indicating the records of the unnecessary information
are calculated in a learning unit from a plurality of keywords attached to the
necessary information and the unnecessary information. Thereafter, a plurality
of keywords attached to each piece of information data input to be estimated are
converted into a vector in a vector generating unit, and an affirmative score signal
and a negative score signal are calculated from the vector and the affirmative
and negative metric signals in a score calculating unit. A value of the affirmative
score signal is increased when many of keywords attached to a corresponding piece
of information data are attached to the necessary information, and a value of the
negative score signal is increased when many of keywords attached to a corresponding
piece of information data are attached to the unnecessary information. Thereafter,
necessity of each piece of information data is calculated from the affirmative
and negative score signals, and the pieces of information data are stored in an
unread data storing unit in order of necessity. Accordingly, information having
a high necessity for the user can be easily retrieved from a large volume of information.
