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        <title>Automatic Community Creation for Abstractive Spoken Conversations Summarization</title>
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    <name type="personal">
        <namePart type="given">Karan</namePart>
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        <namePart type="given">Evgeny</namePart>
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        <namePart type="given">Ali</namePart>
        <namePart type="given">Orkan</namePart>
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    <name type="personal">
        <namePart type="given">Giuseppe</namePart>
        <namePart type="family">Carenini</namePart>
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    <name type="personal">
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    <abstract>Summarization of spoken conversations is a challenging task, since it requires deep understanding of dialogs. Abstractive summarization techniques rely on linking the summary sentences to sets of original conversation sentences, i.e. communities. Unfortunately, such linking information is rarely available or requires trained annotators. We propose and experiment automatic community creation using cosine similarity on different levels of representation: raw text, WordNet SynSet IDs, and word embeddings. We show that the abstractive summarization systems with automatic communities significantly outperform previously published results on both English and Italian corpora.</abstract>
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    <identifier type="doi">10.18653/v1/W17-4506</identifier>
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%0 Conference Proceedings
%T Automatic Community Creation for Abstractive Spoken Conversations Summarization
%A Singla, Karan
%A Stepanov, Evgeny
%A Bayer, Ali Orkan
%A Carenini, Giuseppe
%A Riccardi, Giuseppe
%S Proceedings of the Workshop on New Frontiers in Summarization
%D 2017
%8 sep
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F singla-etal-2017-automatic
%X Summarization of spoken conversations is a challenging task, since it requires deep understanding of dialogs. Abstractive summarization techniques rely on linking the summary sentences to sets of original conversation sentences, i.e. communities. Unfortunately, such linking information is rarely available or requires trained annotators. We propose and experiment automatic community creation using cosine similarity on different levels of representation: raw text, WordNet SynSet IDs, and word embeddings. We show that the abstractive summarization systems with automatic communities significantly outperform previously published results on both English and Italian corpora.
%R 10.18653/v1/W17-4506
%U https://aclanthology.org/W17-4506
%U https://doi.org/10.18653/v1/W17-4506
%P 43-47

Markdown (Informal)

[Automatic Community Creation for Abstractive Spoken Conversations Summarization](https://aclanthology.org/W17-4506) (Singla et al., 2017)

• Automatic Community Creation for Abstractive Spoken Conversations Summarization (Singla et al., 2017)

ACL

• Karan Singla, Evgeny Stepanov, Ali Orkan Bayer, Giuseppe Carenini, and Giuseppe Riccardi. 2017. Automatic Community Creation for Abstractive Spoken Conversations Summarization. In Proceedings of the Workshop on New Frontiers in Summarization, pages 43–47, Copenhagen, Denmark. Association for Computational Linguistics.