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Answer: New problematic phrases can be identified in spam posts.
The main advantage of implementing machine learning for this business case is that new problematic phrases can be identified in spam posts. Unlike the static keyword list currently in use, machine learning algorithms can learn from data and recognize patterns that are indicative of spam, even if specific keywords are not present. This dynamic learning capability allows the system to adapt to new kinds of spam as they emerge, making it far more effective than a static keyword-based approach.
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You work for a company that provides an anti-spam service designed to flag and hide spam posts on various social media platforms. Currently, your company's system uses a list of 200,000 keywords to identify suspected spam posts. If a post contains more than a few of these keywords, it is flagged as spam. However, this approach is limited and static as it relies only on predefined keywords. You want to leverage machine learning to improve the spam detection process by flagging spam posts for human review. What is the main advantage of implementing machine learning in this context?
A
Posts can be compared to the keyword list much more quickly.
B
New problematic phrases can be identified in spam posts.
C
A much longer keyword list can be used to flag spam posts.
D
Spam posts can be flagged using far fewer keywords.
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