| other,8-3-E06-1018,ak | Like most existing approaches it utilizes <term> clustering </term> of <term> word co-occurrences </term> . | #11070 Like most existing approaches it utilizes clustering ofword co-occurrences. | |
| tech,20-7-E06-1018,ak | Offering advantages like reproducability and independency of a given biased <term> gold standard </term> it also enables <term> automatic parameter optimization </term> of the <term> WSI algorithm </term> . | #11169 Offering advantages like reproducability and independency of a given biased gold standard it also enables automatic parameter optimization of theWSI algorithm. | |
| other,6-2-E06-1018,ak | It represents an instantiation of the <term> one sense per collocation observation </term> ( Gale et al. , 1992 ) . | #11049 It represents an instantiation of theone sense per collocation observation (Gale et al., 1992). | |
| other,11-5-E06-1018,ak | The combination with a <term> two-step clustering process </term> using <term> sentence co-occurrences </term> as <term> features </term> allows for accurate results . | #11114 The combination with a two-step clustering process using sentence co-occurrences asfeatures allows for accurate results. | |
| other,8-5-E06-1018,ak | The combination with a <term> two-step clustering process </term> using <term> sentence co-occurrences </term> as <term> features </term> allows for accurate results . | #11111 The combination with a two-step clustering process usingsentence co-occurrences as features allows for accurate results. | |
| other,16-4-E06-1018,ak | This approach differs from other approaches to <term> WSI </term> in that it enhances the effect of the <term> one sense per collocation observation </term> by using <term> triplets of words </term> instead of pairs . | #11089 This approach differs from other approaches to WSI in that it enhances the effect of theone sense per collocation observation by using triplets of words instead of pairs. | |
| tech,7-4-E06-1018,ak | This approach differs from other approaches to <term> WSI </term> in that it enhances the effect of the <term> one sense per collocation observation </term> by using <term> triplets of words </term> instead of pairs . | #11080 This approach differs from other approaches toWSI in that it enhances the effect of the one sense per collocation observation by using triplets of words instead of pairs. | |
| measure(ment),6-6-E06-1018,ak | Additionally , a novel and likewise <term> automatic and unsupervised evaluation method </term> inspired by Schutze 's ( 1992 ) idea of evaluation of <term> word sense disambiguation algorithms </term> is employed . | #11126 Additionally, a novel and likewiseautomatic and unsupervised evaluation method inspired by Schutze's (1992) idea of evaluation of word sense disambiguation algorithms is employed. | |
| other,23-4-E06-1018,ak | This approach differs from other approaches to <term> WSI </term> in that it enhances the effect of the <term> one sense per collocation observation </term> by using <term> triplets of words </term> instead of pairs . | #11096 This approach differs from other approaches to WSI in that it enhances the effect of the one sense per collocation observation by usingtriplets of words instead of pairs. | |
| tech,22-6-E06-1018,ak | Additionally , a novel and likewise <term> automatic and unsupervised evaluation method </term> inspired by Schutze 's ( 1992 ) idea of evaluation of <term> word sense disambiguation algorithms </term> is employed . | #11142 Additionally, a novel and likewise automatic and unsupervised evaluation method inspired by Schutze's (1992) idea of evaluation ofword sense disambiguation algorithms is employed. | |
| tech,7-1-E06-1018,ak | In this paper a novel solution to <term> automatic and unsupervised word sense induction ( WSI ) </term> is introduced . | #11031 In this paper a novel solution toautomatic and unsupervised word sense induction ( WSI ) is introduced. | |
| lr,10-7-E06-1018,ak | Offering advantages like reproducability and independency of a given biased <term> gold standard </term> it also enables <term> automatic parameter optimization </term> of the <term> WSI algorithm </term> . | #11159 Offering advantages like reproducability and independency of a given biasedgold standard it also enables automatic parameter optimization of the WSI algorithm. | |
| tech,15-7-E06-1018,ak | Offering advantages like reproducability and independency of a given biased <term> gold standard </term> it also enables <term> automatic parameter optimization </term> of the <term> WSI algorithm </term> . | #11164 Offering advantages like reproducability and independency of a given biased gold standard it also enablesautomatic parameter optimization of the WSI algorithm. | |
| tech,6-3-E06-1018,ak | Like most existing approaches it utilizes <term> clustering </term> of <term> word co-occurrences </term> . | #11068 Like most existing approaches it utilizesclustering of word co-occurrences. | |
| tech,4-5-E06-1018,ak | The combination with a <term> two-step clustering process </term> using <term> sentence co-occurrences </term> as <term> features </term> allows for accurate results . | #11107 The combination with atwo-step clustering process using sentence co-occurrences as features allows for accurate results. |
