Dharmik Timbadia | Boston University (original) (raw)

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Papers by Dharmik Timbadia

Research paper thumbnail of Spam Text Detection

International Journal of Scientific Research in Computer Science, Engineering and Information Technology

Spam Detection is the process to classify text which contains irrelevant or unsolicited messages ... more Spam Detection is the process to classify text which contains irrelevant or unsolicited messages sent over the internet, typically to a large number of users, for the purposes of advertising, phishing, spreading malware, etc. Text summarization is the technique of converting long text to short. The intention is to make a coherent and fluent summary having only the most points outlined within the document. A USA based machine learning expert which had 13 years of experience and currently teaches people his skills, states his technique has proved to be critical in quickly and accurately summarizing voluminous texts, something which might be expensive and time-consuming if avoided machines. Machine learning models are usually trained to know documents and distil the useful information before outputting the specified summarized texts.

Research paper thumbnail of Spam Text Detection

International Journal of Scientific Research in Computer Science, Engineering and Information Technology

Spam Detection is the process to classify text which contains irrelevant or unsolicited messages ... more Spam Detection is the process to classify text which contains irrelevant or unsolicited messages sent over the internet, typically to a large number of users, for the purposes of advertising, phishing, spreading malware, etc. Text summarization is the technique of converting long text to short. The intention is to make a coherent and fluent summary having only the most points outlined within the document. A USA based machine learning expert which had 13 years of experience and currently teaches people his skills, states his technique has proved to be critical in quickly and accurately summarizing voluminous texts, something which might be expensive and time-consuming if avoided machines. Machine learning models are usually trained to know documents and distil the useful information before outputting the specified summarized texts.

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