Natural Language Processing(NLP)

Natural Language Processing Applications and Challenges

Applications:

• Machine Translation: Convert text from one language to another.
• Spam Detection: Filter the spam emails.
• Summarization: Make the conclusion from the text.
• Information Extraction: Given text, extract important information such as date, timing, etcetra from e-mail.
• Automatic Grading of Essays and Short Answers: Given model answer and student's response, determine score of similarity.

and so on.

Challenges:

• Ambiguity in sentences, as words can have more than one meaning. Example: Red Tape holds up New Bridge, here word "holds" can have two meanings; one is "to support" and other one is "to delay"
• Non-standard English in social media e.g @Messi , #neversaynever as models trained on standard English such as newspapers data.
• Idioms have different meanings.
• Segmentation issues.

and so on.