How to Tune Parameters in Geographical Ontologies Embedding
| Autor: | Michela Bertolotto, Federico Dassereto, Giovanna Guerrini, Laura Di Rocco, Shanley Shaw |
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| Rok vydání: | 2020 |
| Předmět: |
Geospatial analysis
Computer science business.industry Knowledge Bases Context (language use) computer.software_genre Embeddings Geographic information retrieval Geotagging Semantic similarity Question answering Geographic Information Retrieval Embedding Artificial intelligence business Representation (mathematics) computer Natural language processing |
| Zdroj: | LocalRec@SIGSPATIAL |
| DOI: | 10.1145/3423334.3431448 |
| Popis: | Many Natural Language Processing (NLP) tasks, like question answering or analyzing verbatim comments, have started to use word embeddings due to their ability to capture semantic relations between words. Recently, embeddings have been also applied in the geospatial context to represent geospatial ontologies, thanks to their ability to capture semantic similarity. In this paper, we present an analysis of a promising embedding technique particularly suitable for representing hierarchical structures. We conduct a deep technical evaluation of many parameters and their impact on the quality of the representation. |
| Databáze: | OpenAIRE |
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