1. A method of selecting an optimum factor for use in estimating characteristics of a plurality of viewers who view a same content, the method comprising: storing a multi-layered hierarchal factor-list of a plurality of pre-selected factors each of which is a candidate of the optimum factor, the factors being a plurality of attribute words which express attributes of the viewers, the factor list having a plurality of layers; storing a plurality of sets of learned-text information which are relevant to the plurality of attribute words, in sections, on a per-attribute-word basis; extracting a plurality of keywords from the same content; generating a first vector indicative of frequencies with which the plurality of keywords occur in the same content, the first vector having a plurality of elements which the plurality of keywords are allocated, respectively, the elements having values indicative of the frequencies of the plurality of keywords, respectively; for a successively-selected one of the keywords, successively generating a second vector indicative of frequencies with which the plurality of keywords occur in ones of the plurality of sets of learned-text information which ones contain an attribute word identical with the successively-selected keyword, the second vector having a plurality of elements which the plurality of keywords are allocated, respectively, the elements having values indicative of the frequencies of the plurality of keywords, respectively; calculating a similarity score between the first and second vectors on a per-keyword basis; and on a per-layer basis, selecting one of the plurality of factors as the optimum factor, wherein the one factor is associated with a sub-plurality of attribute words, which are on a lower layer than that of the one factor, and which are coincident with at least some of the plurality of keywords, so that a dispersion level indicative of how the similarity scores calculated for the sub-plurality of attribute words are dispersed therewithin can be substantially the maximum among the plurality of factors on the same layer, and selecting the sub-plurality of attribute words as optimum attribute words for the optimum factor.