| other,9-1-P05-1018,ak | problem of automatic assessment of <term> | local coherence | </term> . We present a novel <term> entity-based | #8601 This paper considers the problem of automatic assessment oflocal coherence. | |
| other,4-2-P05-1018,ak | coherence </term> . We present a novel <term> | entity-based representation of discourse | </term> which is inspired by <term> Centering | #8608 We present a novelentity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. | |
| other,12-2-P05-1018,ak | discourse </term> which is inspired by <term> | Centering Theory | </term> and can be computed automatically | #8616 We present a novel entity-based representation of discourse which is inspired byCentering Theory and can be computed automatically from raw text. | |
| other,20-2-P05-1018,ak | can be computed automatically from <term> | raw text | </term> . We view <term> coherence assessment | #8624 We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically fromraw text. | |
| tech,2-3-P05-1018,ak | from <term> raw text </term> . We view <term> | coherence assessment | </term> as a <term> ranking learning problem | #8629 We viewcoherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. | |
| tech,6-3-P05-1018,ak | <term> coherence assessment </term> as a <term> | ranking learning problem | </term> and show that the proposed <term> discourse | #8633 We view coherence assessment as aranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. | |
| other,14-3-P05-1018,ak | problem </term> and show that the proposed <term> | discourse representation | </term> supports the effective learning of | #8641 We view coherence assessment as a ranking learning problem and show that the proposeddiscourse representation supports the effective learning of a ranking function. | |
| tech,22-3-P05-1018,ak | supports the effective learning of a <term> | ranking function | </term> . Our experiments demonstrate that | #8649 We view coherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of aranking function. | |
| measure(ment),10-4-P05-1018,ak | model achieves significantly higher <term> | accuracy | </term> than a state-of-the-art <term> coherence | #8662 Our experiments demonstrate that the induced model achieves significantly higheraccuracy than a state-of-the-art coherence model. | |
| other,14-4-P05-1018,ak | accuracy </term> than a state-of-the-art <term> | coherence model | </term> . This paper presents a <term> corpus | #8666 Our experiments demonstrate that the induced model achieves significantly higher accuracy than a state-of-the-artcoherence model. |
