1. A computer implemented method of information retrieval, comprising: parsing a corpus to identify instances of wordforms within each document of the corpus; performing a morphological tokenization on the wordforms to convert the wordforms into morphemes by separating affixes from their stems; generating a morpheme-by-document matrix based at least in part on a number of instances of the affixes and the stems within each document of the corpus, wherein the morpheme-by-document matrix accounts for information related to past tense and present tense inflections by separately enumerating the instances of the affixes from the instances of the stems; applying a weighting function to attribute-values within the morpheme-by-document matrix to generate a weighted morpheme-by-document matrix, wherein applying the weighting function includes: applying the weighting function to the attribute-values of the stems; and applying the weighting function to the attribute-values of the affixes separately from the attribute-values of the stems to separately account for relative importance of the affixes; generating at least one lower rank approximation matrix by factorizing the weighted morpheme-by-document matrix; and retrieving information with reference to the at least one lower rank approximation matrix.
1. A computer implemented method of information retrieval, comprising: parsing a corpus to identify instances of wordforms within each document of the corpus; performing a morphological tokenization on the wordforms to convert the wordforms into morphemes by separating affixes from their stems; generating a morpheme-by-document matrix based at least in part on a number of instances of the affixes and the stems within each document of the corpus, wherein the morpheme-by-document matrix accounts for information related to past tense and present tense inflections by separately enumerating the instances of the affixes from the instances of the stems; applying a weighting function to attribute-values within the morpheme-by-document matrix to generate a weighted morpheme-by-document matrix, wherein applying the weighting function includes: applying the weighting function to the attribute-values of the stems; and applying the weighting function to the attribute-values of the affixes separately from the attribute-values of the stems to separately account for relative importance of the affixes; generating at least one lower rank approximation matrix by factorizing the weighted morpheme-by-document matrix; and retrieving information with reference to the at least one lower rank approximation matrix. 3. The computer implemented method of claim 1 , wherein generating the at least one lower rank approximation matrix by factorizing the weighted morpheme-by-document matrix comprises: performing a singular value decomposition (SVD) on the weighted morpheme-by-document matrix; generating a morpheme-by-concept matrix; and generating a document-by-concept matrix.