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Rights Holder and Contact
Vanhook, Christopher J.; Kim, Juhwan; Damte, Selamawit
Description
Predicting Mass Casualty Events From 911 Data Streams aims to provide dispatchers with a usable tool that alerts of any potentially occurring events while allowing them to monitor call conditions and real-time traffic alerts. The data involved was call data provided by the Communications Venture Corporation. This project was accomplished as part of the DSE MAS 24 program, for the class of DSE260. Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp) This project relies on external software packages, modules/libraries, or programs, use of which may carry specific license requirements. Users should comply with any licenses specified within the contents of this project. Vanhook, Christopher J.; Kim, Juhwan; Damte, Selamawit; Zaslavsky, Ilya (2024). Predicting Mass Casualty Events from 911 Data Streams. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0MC907C
Type
dataset
Identifier
ark:/20775/bb1855512k
Language
English
Subject
Telephone--Emergency reporting systems Data Science & Engineering Master of Advanced Study (DSE MAS) Algorithm: Unsupervised learning Event prediction Streaming data Machine learning Capstone projects DSE MAS - 2024 Cohort
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