Notice of Violation of IEEE Publication Principles - Detecting Terror-Related Activities on the Web with Using Data Mining Techniques

Hosseinpour, Mahsa; Omidvar, M.N.

doi:10.1109/iccee.2009.46

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…The Web pages downloaded are fed as the input to the Vector Generator module as shown in Figure 1, which converts the pages into vectors of weighted terms (each page into a vector). These vectors are stored for future processing in the vector of Terrorist Transaction in DB [9]. The unsupervised clustering is performed on these vectors.…”

Section: Learning Typical Terrorist Behaviormentioning

confidence: 99%

“…The document D is represented by the n-dimensional vector V= (v 1 , v 2 , v 3 …v n) where v i represents the frequency-based weight of term i in D. The similarity between the two documents represented as vectors may be computed by using one of the known vector distance measuring methods such as Euclidian distance or Cosine. The cosine similarity measure is commonly used to estimate the similarity between an accessed Web page and a given set of terrorists' topic of interest [9].…”

Section: Vector-space Modelmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Terrorist Network Mining: Current Trends and Opportunities

Chaurasia¹

2012

IJCSES

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Section: Learning Typical Terrorist Behaviormentioning

confidence: 99%

Section: Vector-space Modelmentioning

confidence: 99%

A Survey on Terrorist Network Mining: Current Trends and Opportunities

Chaurasia¹

2012

IJCSES

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“…The Web pages downloaded are fed as the input to the Vector Generator module which converts the pages into vectors of weighted terms (each page into a vector). These vectors are stored for future processing in the vector of Terrorist Transaction in DB [9].…”

Section: Learning Typical Terrorist Behaviormentioning

confidence: 99%

“…The cosine similarity measure is commonly used to estimate the similarity between an accessed Web page and a given set of terrorists' topic of interest [9].…”

Section: Vector-space Modelmentioning

confidence: 99%

Exploring the Current Trends and Future Prospects in Terrorist Network Mining

Chaurasia¹,

Dhakar²,

Chharia³

et al. 2012

Computer Science &Amp; Information Technology (CS &Amp; IT)

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Online Terrorism Detection Using Webdata Mining

K²,

M³

2020

IICT

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Technology growth in facebook, whatsapp, instagram has become famous and widely used in diverse social media groups. The intention of facebook is to make the universe widely open and to stay connected. The recent mission of facebook is to stay connected with friends, colleagues, family through sharing photos, videos, stories etc. to show the daily events in the world, which provides the mean to share and express the feelings on what matters to them. Cross platform Instant messaging applications like Telegram and WhatsApp Messenger that smart phone users to establish a ubiquitous technology to exchange text, image, video and audio messages for free. This flexible technology explores more opportunities for risk and benefit for the modern era. Terrorism has increased in certain fragile parts of the world and they attack remotely. New technologies like Artificial intelligence, Machine learning autonomous and semi-autonomous systems are used by terrorist group to attack the network. These groups use social media weapons like facebook, whatsapp, Instagram to spread their information on the social network. It is essential to detect, pre-empt, prevent and eliminate the terrorism through technological spear. Terrorist groups are utilizing the internet as a platform together and convince the sin less people to take part in terrorist activities by infuriating them through web pages that inspired is enchanted individuals to take part in terrorist activities. The detection of terrorist activities needs enormous human effort. To reduce the human effort, our implement system detects the terrorist groups in social media using data mining algorithm. The intention of this work is to is to reduce the terrorism spread and to remove the terrorism related accounts effortlessly.

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Notice of Violation of IEEE Publication Principles - Detecting Terror-Related Activities on the Web with Using Data Mining Techniques

Cited by 3 publications

References 7 publications

A Survey on Terrorist Network Mining: Current Trends and Opportunities

A Survey on Terrorist Network Mining: Current Trends and Opportunities

Exploring the Current Trends and Future Prospects in Terrorist Network Mining

Online Terrorism Detection Using Webdata Mining

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