| document descriptors ( keywords ) </term> | than | single <term> words </term> are . This leads | #20040 One of the distinguishing features of a more linguistically sophisticated representation of documents over a word set based representation of them is that linguistically sophisticated units are more frequently individually good predictors of document descriptors (keywords)than single words are. | |
| from individual <term> phrases </term> rather | than | from the <term> weighted sum </term> of a <term> | #20058 This leads us to consider the assignment of descriptors from individual phrases rather than from the weighted sum of a word set representation. | |
| becomes a crucial issue recently . Rather | than | using <term> length-based or translation-based | #20543 Rather than using length-based or translation-based criterion, a part-of-speech-based criterion is proposed. | |
| <term> kanji-kana characters </term> is greater | than | that of <term> erroneous chains </term> . From | #20709 In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains. | |
| theoretical accounts actually have worse coverage | than | accounts based on processing . Finally | #21186 This paper reviews the theoretical literature, and shows why many of the theoretical accounts actually have worse coverage than accounts based on processing. |
