Tauchmann, Christopher ; Arnold, Thomas ; Hanselowski, Andreas ; Meyer, Christian M. ; Mieskes, Margot (2018)
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous Data.
Miyazaki, Japan
Conference or Workshop Item, Bibliographie
Abstract
Automatic summarization has so far focused on datasets of ten to twenty rather short documents of mostly news articles. But automatic systems could in theory analyze hundreds of documents from a range of sources and provide an overview to the interested reader. Such a summary would ideally present the most general issues in a specific topic and allow for more in-depth information on specific aspects within said topic. In this paper, we present a new approach for creating hierarchical summarization corpora by first, extracting relevant content from large, heterogeneous document collections using crowdsourcing and second, ordering the relevant information hierarchically by trained annotators. Our resulting corpus can be used to develop and evaluate hierarchical summarization systems.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2018 |
| Creators: | Tauchmann, Christopher ; Arnold, Thomas ; Hanselowski, Andreas ; Meyer, Christian M. ; Mieskes, Margot |
| Type of entry: | Bibliographie |
| Title: | Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous Data |
| Language: | English |
| Date: | May 2018 |
| Publisher: | European Language Resources Association |
| Book Title: | Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC) |
| Event Location: | Miyazaki, Japan |
| URL / URN: | http://www.lrec-conf.org/proceedings/lrec2018/summaries/252.... |
| Corresponding Links: | |
| Abstract: | Automatic summarization has so far focused on datasets of ten to twenty rather short documents of mostly news articles. But automatic systems could in theory analyze hundreds of documents from a range of sources and provide an overview to the interested reader. Such a summary would ideally present the most general issues in a specific topic and allow for more in-depth information on specific aspects within said topic. In this paper, we present a new approach for creating hierarchical summarization corpora by first, extracting relevant content from large, heterogeneous document collections using crowdsourcing and second, ordering the relevant information hierarchically by trained annotators. Our resulting corpus can be used to develop and evaluate hierarchical summarization systems. |
| Uncontrolled Keywords: | reviewed;AIPHES_corpus;AIPHES_area_c1 |
| Identification Number: | TUD-CS-2018-0007 |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Ubiquitous Knowledge Processing DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Research Training Group 1994 Adaptive Preparation of Information from Heterogeneous Sources |
| Date Deposited: | 14 Dec 2017 14:24 |
| Last Modified: | 15 Oct 2018 09:10 |
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