Humanitarian Assistance Ontology Implementation during Disaster Management in Chennai Flood-2015 Using Text Mining Techniques 1 C. Anbarasi and 2 P. Mayilvahanan 1 Vels University, Pallavaram, Chennai. [email protected]2 Department of Computer Applications, Vels University, Chennai, Tamil Nadu, India. [email protected]Abstract A disaster management plan for the city is in the works, following alarm over a series of earthquakes that have recently occurred in Nepal, and the tremors felt in various parts of the country, flood disaster in Chennai 2015. The main task of the research work is being focused on constructing an application using data mining techniques and algorithms during disaster situation The Commissionerate of Revenue Administration in association with Chennai Corporation and Chennai district collectorate will work together on this, according to sources. Chennai is yet to have a comprehensive disaster management plan, which includes predefined roles and responsibilities with specific tasks for each official. The disaster management plan will include detailed mapping of safest escape routes and resources for facilitating rescue and relief operations. The lack of a disaster management plan has previously led to a delay in relief and rescue work after major disasters such as tsunami and flood in the city. We will start collecting data on resources at the ward level. Chennai Corporation has 200 wards covering an area of 426 sq km. Ward level mapping was done after the tsunami. Some of the earlier works pertaining to mapping for disaster preparedness are not relevant after the boundaries of wards and zones changed following expansion of the city, said a disaster International Journal of Pure and Applied Mathematics Volume 116 No. 21 2017, 729-739 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu 729
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Humanitarian Assistance Ontology Implementation during ... · humanitarian assistance in specific places to avoid delay and confusion in humanitarian responses in real t ime. The
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Step 5 - data is stored in the table for the terms that have similarity frequency
5. Implementation
The word cloud and text mining techniques are used in Chennai–flood 2015
data set and the results are generated. The below screen shots shows that the
text mining libraries are implemented successfully. Comments from social
media are captured, clustered, classified, evaluated and reports related to crisis
response is generated.
Figure 3: Disaster Management System Home Page
Figure 4: Database - Chennai Flood 2015
Figure 5: Display of Calculation of Percentage from Various Respondents
6. Future Enhancement
The system evaluation results demonstrate the effectiveness and efficiency of
our proposed approaches. During the system implementation and assessment
process, the users provided suggestions, limitations and possible enhancements.
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Our future efforts will be focusing on the following tasks: evaluation with
images and video files. To develop more accurate and fast application tool
which captures the current user‟s comment and provide them with actionable
answers dynamically. The feedback from our users is positive and suggests that
our system can be used to share the valuable actionable information and to
pursue more complex tasks.
7. Conclusion
This research work discusses about the steps of HAO implementation during
disaster management in Chennai flood 2015. The extraction of structured data
from unstructured data conveys the demographic details of the affected people.
From this proposed methodology, an application tool is developed on inductive
queries and comments collected from social media during Chennai flood – dec‟
2015. Using text mining libraries and word cloud the data set is classified and
by using the logical rules the implementation of classification algorithm helps
the data to be structured. From the pool of information, we are able to convert
raw data into meaningful information. This meaningful information helps the
decision makers in speedy crisis response action during a disaster situation.
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