| tech,3-1-C04-1116,bq | smaller and more robust . We present a <term> | text mining method | </term> for finding <term> synonymous expressions | #6095 We present atext mining method for finding synonymous expressions based on the distributional hypothesis in a set of coherent corpora. |
| other,8-1-C04-1116,bq | text mining method </term> for finding <term> | synonymous expressions | </term> based on the <term> distributional | #6100 We present a text mining method for findingsynonymous expressions based on the distributional hypothesis in a set of coherent corpora. |
| other,13-1-C04-1116,bq | synonymous expressions </term> based on the <term> | distributional hypothesis | </term> in a set of coherent <term> corpora | #6105 We present a text mining method for finding synonymous expressions based on thedistributional hypothesis in a set of coherent corpora. |
| tech,12-2-C04-1116,bq | improve the <term> accuracy </term> of a <term> | term aggregation system | </term> using each author 's text as a coherent | #6126 This paper proposes a new methodology to improve the accuracy of aterm aggregation system using each author's text as a coherent corpus. |
| other,11-4-C04-1116,bq | assumption , most of the words with similar <term> | context features | </term> in each author 's <term> corpus </term> | #6169 According to our assumption, most of the words with similarcontext features in each author's corpus tend not to be synonymous expressions. |
| other,22-4-C04-1116,bq | 's <term> corpus </term> tend not to be <term> | synonymous expressions | </term> . Our proposed method improves the | #6180 According to our assumption, most of the words with similar context features in each author's corpus tend not to besynonymous expressions. |
| tech,8-5-C04-1116,bq | improves the <term> accuracy </term> of our <term> | term aggregation system | </term> , showing that our approach is successful | #6191 Our proposed method improves the accuracy of ourterm aggregation system, showing that our approach is successful. |
