Ontology-Grounded Topic Modeling for Climate Science Research
dc.contributor.author | Sleeman, Jennifer | |
dc.contributor.author | Finin, Tim | |
dc.contributor.author | Halem, Milton | |
dc.date.accessioned | 2018-10-18T13:47:54Z | |
dc.date.available | 2018-10-18T13:47:54Z | |
dc.date.issued | 2018-10-08 | |
dc.description | Emerging Topics in Semantic Technologies. ISWC 2018 Satellite Events | en_US |
dc.description.abstract | In scientific disciplines where research findings have a strong impact on society, reducing the amount of time it takes to understand, synthesize and exploit the research is invaluable. Topic modeling is an effective technique for summarizing a collection of documents to find the main themes among them and to classify other documents that have a similar mixture of co-occurring words. We show how grounding a topic model with an ontology, extracted from a glossary of important domain phrases, improves the topics generated and makes them easier to understand. We apply and evaluate this method to the climate science domain. The result improves the topics generated and supports faster research understanding, discovery of social networks among researchers, and automatic ontology generation. | en_US |
dc.description.sponsorship | This work was partially supported by a grant of computational resource services from the Microsoft AI for Earth program and a gift from the IBM AI Horizons Network. | en_US |
dc.description.uri | https://arxiv.org/abs/1807.10965 | en_US |
dc.description.uri | https://drive.google.com/file/d/15xRhtX59tblcrCYxcPB3QJ6_L_lbnRU3/view | |
dc.format.extent | 12 pages | en_US |
dc.genre | conference papers and proceedings preprints | en_US |
dc.identifier | doi:10.13016/M2V698G6C | |
dc.identifier.citation | Jennifer Sleeman, Tim Finin, Milton Halem, Ontology-Grounded Topic Modeling for Climate Science Research, Emerging Topics in Semantic Technologies. ISWC 2018 Satellite Events, https://ebiquity.umbc.edu/paper/html/id/831/Ontology-Grounded-Topic-Modeling-for-Climate-Science-Research | en_US |
dc.identifier.uri | http://hdl.handle.net/11603/11599 | |
dc.language.iso | en_US | en_US |
dc.publisher | AKA Verlag, Berlin | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
dc.subject | topic modeling | en_US |
dc.subject | ontology | en_US |
dc.subject | climate science | en_US |
dc.subject | explainability | en_US |
dc.subject | UMBC Ebiquity Research Group | en_US |
dc.title | Ontology-Grounded Topic Modeling for Climate Science Research | en_US |
dc.type | Text | en_US |
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