E-ware: a big data system for the incremental discovery of spatio-temporal events from microblogs-Reference-Cited by-同舟云学术

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E-ware: a big data system for the incremental discovery of spatio-temporal events from microblogs

Published:2022-06-25 Issue: Volume: Page:
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Afyouni Imad^ORCID,Khan Aamir,Al Aghbari Zaher

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-022-04104-4.pdf

Reference59 articles.

1. Adedoyin-Olowe M, Gaber MM, Dancausa CM, Stahl F, Gomes JB (2016) A rule dynamics approach to event detection in twitter with its application to sports and politics. Expert Syst Appl 55:351–360

2. Afyouni I, Aghbari ZA, Razack RA (2022) Multi-feature, multi-modal, and multi-source social event detection: A comprehensive survey. Inf Fusion 79:279–308

3. Ahuja A, Baghudana A, Lu W, Fox EA, Reddy CK (2019) Spatio-temporal event detection from multiple data sources. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp 293–305. Springer

4. Ai W, Li K, Li K (2018) An effective hot topic detection method for microblog on spark. Appl Soft Comput 70:1010–1023

5. Alkouz B, Aghbari ZA (2020) Snsjam: road traffic analysis and prediction by fusing data from multiple social networks. Inf Process Manag 57(1):102139

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1. Harnessing Extracted Social Media Events for Personalized Travel Sequences;Proceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising;2023-11-13

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