A novel spatio-temporal similarity algorithm adapted to typhoon disaster cases

Zhou, Xi; Wang, Fei; Wang, Chaolin; Zheng, Xuan; Zheng, Fuda; Li, Li

doi:10.1109/geoinformatics.2015.7378654

Cited by 1 publication

(1 citation statement)

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“…This signi cant and authentic data provides indispensable information in order to actually visualize the change in the political events happening over a speci c geographical area and time period [13][14]. These authentic news archives are not well categorized or arranged, thereby making it highly challenging during the process of determining useful information that are more correlated to interesting change in political events happening in a region [15]. It provided high valuable information source as it inherits purposeful and rich content as it is carefully captured by specialists, who have more expertise in investigating the change in the political events occurring in a speci c region.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Analysis of Archived Web News for Precise Political Event Detection and Impact Analysis in India's Southern States

Muthamizharasan¹,

Ponnusamy²

2022

Preprint

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The national political system has the directly impacts the economy. Every political party has their own economic policies. This has the major impact on the economic stability of the nation. Sometimes, few political parties rule either the state or national Governments. Their policies directly reflect in the state or national level financial systems. In general political parties, pay more attention to the state in which they control or aspire to establish their party's rule. Political discourse has an unspoken impact on the state's financial stability. Data from unstructured political events (1200 records) produced for accurate political event prediction; data was pulled from the archives of web news accumulated over the last 5 years to better understand the impact of such impact discovered in this article. This recommended work includes the advantages of Spatiotemporal Analysis of Web News Archives for forecasting network features modeled through political events and converting them into possible information based on natural language processing qualities. The suggested approach constructs a spatial analysis based on hotspots for estimating the sequence of political events in India. Lastly, the resulting data is nurtured into several classifiers for a more reliable prediction and identification procedure. This proposed technique reached a maximum frequency of 78.21 percent and 93.58 percent, respectively, when compared to the Random forest method and the K-neighbor neighbour (KNN) algorithms.

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Section: Introductionmentioning

confidence: 99%