Implementing LDA Topic Modelling Technique to Study User Reviews in Tourism
Extracting valuable information from unstructured text is a significant difficulty in today's culture due to the ever-increasing proliferation of texts, most of which are generated via online social networks in the form of consumer-generated media. Despite this difficulty, natural language proc...
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| Vydáno v: | International Conference on Parallel, Distributed and Grid Computing (PDGC ...) s. 357 - 360 |
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| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
25.11.2022
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| Témata: | |
| ISBN: | 9781665454001, 1665454008 |
| ISSN: | 2573-3079 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Extracting valuable information from unstructured text is a significant difficulty in today's culture due to the ever-increasing proliferation of texts, most of which are generated via online social networks in the form of consumer-generated media. Despite this difficulty, natural language processing algorithms are being developed rapidly, including topic modelling approaches for discovering latent subjects in text documents like online reviews. As a result, topic modelling methodologies have not grown in favour of the tourist industry yet. So Authors decided to work on a tourism dataset. The results show us the importance of topic keywords concerning the tourism dataset the best perplexity score we get us with the D3 Dataset was -7.9947. |
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| ISBN: | 9781665454001 1665454008 |
| ISSN: | 2573-3079 |
| DOI: | 10.1109/PDGC56933.2022.10053153 |