Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels
| Authors |
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| Publication date | 2020 |
| Host editors |
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| Book title | The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature |
| Book subtitle | Co-located with the 28th International Conference on Computational Linguistics COLING’2020 : COLING 2020 : proceedings : December 12, 2020, Barcelona, Spain, (Online) |
| ISBN (electronic) |
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| Event | 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature |
| Pages (from-to) | 147-155 |
| Number of pages | 9 |
| Publisher | International Committee on Computational Linguistics |
| Organisations |
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| Abstract |
Environmental factors determine the smells we perceive, but societal factors factors shape the importance, sentiment and biases we give to them. Descriptions of smells in text, or as we call them `smell experiences', offer a window into these factors, but they must first be identified. To the best of our knowledge, no tool exists to extract references to smell experiences from text. In this paper, we present two variations on a semi-supervised approach to identify smell experiences in English literature. The combined set of patterns from both implementations offer significantly better performance than a keyword-based baseline.
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| Document type | Conference contribution |
| Note | Version v2 also available. |
| Language | English |
| Related dataset | Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels |
| Published at | https://www.aclweb.org/anthology/2020.latechclfl-1.18 |
| Downloads |
2020.latechclfl-1.18v1
(Final published version)
2020.latechclfl-1.18v2
(Other version)
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| Permalink to this page | |
