A Study on a Combined Model in Business Intelligence for Improving Electronic Insurance

Bazargani, Mahdi; Namazi, Elnaz

doi:10.4018/ijbir.2015010104

Security countermeasures in the cyber-world

Andreea

¹

,

Al-Nemrat

²

2016

2016 IEEE International Conference on Cybercrime and Computer Forensic (ICCCF)

0

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Abstract-Companies and individuals are depending more and more on technology through increasingly automated processes, the use of IoT and daily activities performed through the use of internet, mobile devices and other concepts that the technological evolution deployed. But in the context of the rapid technological progress, the cyber-threats become a serious challenge that requires immediate, continuous action. As cybercrime poses a permanent, increasing threat, corporate and individual users of the cyber-space are constantly struggling to ensure an acceptable level of security over their assets. Based on the analysis of 4,785 attacks deployed in the recent years all over the world, this paper outlines the correlations and patterns identified, under the final objective of defining security countermeasures that organisations from certain business sectors could implement in order to focus their limited resources and budget on mitigating the right risks.

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Political Sentiment Mining

Bele

¹

,

Panigrahi

²

,

Srivastava

³

2020

Cognitive Analytics

0

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Investigations on sentiment mining are mostly ensued in the English language. Due to the characteristics of the Indian languages tools and techniques used for sentiment mining in the English language cannot be applied directly to text in Hindi languages. The objective of this paper is to extract the political sentiment at the document-level from Hindi blogs. The authors could not find any literature about extracting sentiments at the document-level from Hindi blogs. They extracted opinion about one of India's very famous leaders who was a prominent face in the national election of 2014. They prepared the datasets from Hindi blogs reviews. They purposed the lexicon and machine learning technique to classify the sentiment. Their purposed method used four steps: (1) Crawling and preprocessing the blog reviews; (2) Extracting reviews relevant to the query using the Vector Space Model (VSM); (3) Identifying sentiment at the document level using the Lexicon method, and (4) Measuring the result using the Machine learning technique. Their experimental result demonstrates the effectiveness of our algorithms.

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Political Sentiment Mining

Bele

¹

,

Panigrahi

²

,

Srivastava

³

2017

International Journal of Business Intelligence Research

2

0

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Investigations on sentiment mining are mostly ensued in the English language. Due to the characteristics of the Indian languages tools and techniques used for sentiment mining in the English language cannot be applied directly to text in Hindi languages. The objective of this paper is to extract the political sentiment at the document-level from Hindi blogs. The authors could not find any literature about extracting sentiments at the document-level from Hindi blogs. They extracted opinion about one of India's very famous leaders who was a prominent face in the national election of 2014. They prepared the datasets from Hindi blogs reviews. They purposed the lexicon and machine learning technique to classify the sentiment. Their purposed method used four steps: (1) Crawling and preprocessing the blog reviews; (2) Extracting reviews relevant to the query using the Vector Space Model (VSM); (3) Identifying sentiment at the document level using the Lexicon method, and (4) Measuring the result using the Machine learning technique. Their experimental result demonstrates the effectiveness of our algorithms.

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A Study on a Combined Model in Business Intelligence for Improving Electronic Insurance

Cited by 3 publications

References 5 publications

Security countermeasures in the cyber-world

Security countermeasures in the cyber-world

Political Sentiment Mining

Political Sentiment Mining

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