Brian Mac Namee


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Diverging Divergences: Examining Variants of Jensen Shannon Divergence for Corpus Comparison Tasks
Jinghui Lu | Maeve Henchion | Brian Mac Namee
Proceedings of the 12th Language Resources and Evaluation Conference

Jensen-Shannon divergence (JSD) is a distribution similarity measurement widely used in natural language processing. In corpus comparison tasks, where keywords are extracted to reveal the divergence between different corpora (for example, social media posts from proponents of different views on a political issue), two variants of JSD have emerged in the literature. One of these uses a weighting based on the relative sizes of the corpora being compared. In this paper we argue that this weighting is unnecessary and, in fact, can lead to misleading results. We recommend that this weighted version is not used. We base this recommendation on an analysis of the JSD variants and experiments showing how they impact corpus comparison results as the relative sizes of the corpora being compared change.


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The Effect of Sensor Errors in Situated Human-Computer Dialogue
Niels Schütte | John Kelleher | Brian Mac Namee
Proceedings of the Third Workshop on Vision and Language


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Referring Expression Generation Challenge 2008 DIT System Descriptions (DIT-FBI, DIT-TVAS, DIT-CBSR, DIT-RBR, DIT-FBI-CBSR, DIT-TVAS-RBR)
John D. Kelleher | Brian Mac Namee
Proceedings of the Fifth International Natural Language Generation Conference