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            <title>Proceedings of the 2nd Workshop on New Frontiers in Summarization</title>
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            <namePart type="given">Lu</namePart>
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    <abstract>Concept maps are visual summaries, structured as directed graphs: important concepts from a dataset are displayed as vertexes, and edges between vertexes show natural language descriptions of the relationships between the concepts on the map. Thus far, preliminary attempts at automatically creating concept maps have focused on building static summaries. However, in interactive settings, users will need to dynamically investigate particular relationships between pairs of concepts. For instance, a historian using a concept map browser might decide to investigate the relationship between two politicians in a news archive. We present a model which responds to such queries by returning one or more short, importance-ranked, natural language descriptions of the relationship between two requested concepts, for display in a visual interface. Our model is trained on a new public dataset, collected for this task.</abstract>
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%0 Conference Proceedings
%T Summarizing Relationships for Interactive Concept Map Browsers
%A Handler, Abram
%A Ganeshkumar, Premkumar
%A O’Connor, Brendan
%A AlTantawy, Mohamed
%Y Wang, Lu
%Y Cheung, Jackie Chi Kit
%Y Carenini, Giuseppe
%Y Liu, Fei
%S Proceedings of the 2nd Workshop on New Frontiers in Summarization
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F handler-etal-2019-summarizing
%X Concept maps are visual summaries, structured as directed graphs: important concepts from a dataset are displayed as vertexes, and edges between vertexes show natural language descriptions of the relationships between the concepts on the map. Thus far, preliminary attempts at automatically creating concept maps have focused on building static summaries. However, in interactive settings, users will need to dynamically investigate particular relationships between pairs of concepts. For instance, a historian using a concept map browser might decide to investigate the relationship between two politicians in a news archive. We present a model which responds to such queries by returning one or more short, importance-ranked, natural language descriptions of the relationship between two requested concepts, for display in a visual interface. Our model is trained on a new public dataset, collected for this task.
%R 10.18653/v1/D19-5414
%U https://aclanthology.org/D19-5414
%U https://doi.org/10.18653/v1/D19-5414
%P 111-115

Markdown (Informal)

[Summarizing Relationships for Interactive Concept Map Browsers](https://aclanthology.org/D19-5414) (Handler et al., 2019)

• Summarizing Relationships for Interactive Concept Map Browsers (Handler et al., 2019)

ACL

• Abram Handler, Premkumar Ganeshkumar, Brendan O’Connor, and Mohamed AlTantawy. 2019. Summarizing Relationships for Interactive Concept Map Browsers. In Proceedings of the 2nd Workshop on New Frontiers in Summarization, pages 111–115, Hong Kong, China. Association for Computational Linguistics.