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 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 the 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 the 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.