Abstract:
Terrorism has deep roots in some places. Increasing terrorism has made it vital to control and stop its spread early. As stated, internet talks and videos spread terrorism. Terrorist organizations utilize the internet to brainwash people and recruit helpless people through controversial websites.
We provide an efficient web data mining approach to discover such web properties and flag them for human evaluation. Data mining extracts meaningful patterns from massive data sets and maximizes results. Combining data and web mining can speed up system development.
Text mining methods let us scan and extract meaningful content from unstructured data in web mining. Text mining finds patterns, keywords, and useful information in unstructured texts. Web and data mining systems are commonly utilized for text mining.
Web mining algorithms scan and mine unstructured web pages and text data from the internet, while data mining algorithms manipulate ordered data sets efficiently. varied platform websites have varied data structures, making them hard to understand for one algorithm.
We must employ effective web mining algorithms to mine this massive amount of web data since it is not possible to design a different algorithm for each web technology. HTML is used to create web pages with images, videos, and other content.
Thus, we propose using smart web mining algorithms to mine web page text for terrorism relevance. In this method, we can evaluate websites for terrorism promotion. This technique helps anti-terrorism organizations and search engines classify websites. They are categorized and flagged for human inspection based on their field relevance.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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