Using big data values to enhance social event detection pattern

Cherichi, Soumaya; Larodec, Rim Faiz

doi:10.1109/aiccsa.2016.7945732

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…They paid attention to the importance of public-private partnerships, swift trust, information quality, critical infrastructure resilience, community resilience and resource resilience using context of Nepal. Cherichi & Larodec ( 2016) proposed an event detection system based on data obtained from twitter. The aim of this system is determine new events, recognize temporal indicators and classify significant events using big data values in the case of social events.…”

Section: Searching Based On "Big Data" Stringmentioning

confidence: 99%

A Literature Review on Big Data and Social Media Usage in Disaster Management

Dereli

Çelik

Çetinkaya

2018

Afet Ve Risk Dergisi

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Most of the disaster management activities are naturally related to traditional operation research and management science applications. But recently, big data information technology and social media in particular has become an integral part of disaster management. Relevant information taken from social media and the intelligent web has increased the situational awareness of decision makers. Disaster management decisions have important impacts on; the safety of disaster victims, environment, economic systems, organizations etc. Reliable, timely, consistent, sufficient and qualified information is critical in the phases of disaster management. In this study, a literature review is conducted considering big data and social media in the light of disaster management and specifically disaster relief.

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Section: Searching Based On "Big Data" Stringmentioning

confidence: 99%

A Literature Review on Big Data and Social Media Usage in Disaster Management

Dereli

Çelik

Çetinkaya

2018

Afet Ve Risk Dergisi

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“…[6] Apart from these the social media can also be used for impact prediction as proposed by Soumya et. al [7]. They have made a new event detection approach my combining the linguistic feature of twitter.…”

mentioning

confidence: 99%

Disaster Impact Mitigation using KDD and Support Vector Machine algorithms

Aravindhar¹,

Sushmitha²,

Padmaveni³

2018

EAI Endorsed Transactions on Energy Web

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Disasters such as Hurricanes, Typhoons, Floods and earthquakesare not good for the society since it causes serious damage for the society. A natural disaster causes loss in property as well as in life of victims. The victims need immediate help once they are affected by the disaster. The immediate need are rescue, food and communications. The survey says victims of recent disaster were unable to get instant communication regarding the evacuation path and other help from authorities for remedial action. This can be overcome with our proposed idea of having a database of area wise population along with the pre-disaster and post-disaster satellite images of the disaster affected area. Knowledge Discovery in Databases (KDD) is used in data pre-processing and to extract knowledge from the database. Support vector machine(SVM) is used to classify the disaster effect with the pre-disaster and post-disaster satellite images as input. The idea is implemented and tested with sample data and has given impressive results

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