NLP-A DIGITAL WORLD OF LANGUAGES AND EMOTIONS
Natural Language Processing is one of the very interesting and interactive domain of research in Artificial Intelligence. In 1950 Alan Turing who is called as founder of computer science, mathematician, philosopher, code cracker, strange visionary proposed an experiment to check the ability to carry on believable conversation could be served as a test for a truly intelligent machine. Let’s go through the some of the components of Natural Language Processing.
Sentiment Analysis: You must remember during 15 days of Christmas just typing a ‘Merry’ an emoticon of Santa and or Christmas tree arrives automatically in front of your curser of mobile. Emoticons are the only component in the text that expresses some positive and negative sentiments. It is been observed that when an emoticons were removed from the tweeter the sentiments of those tweets became neutral or unclear Its just about one of the component of natural language processing which is “Sentiment Analysis”.
Machine translator: There are 6500 spoken languages in the world. As far as India as concern the number of languages get restricted to 22. Google translator is a language processing tool of Google which assist in not only understanding the word but also in understanding the meaning too. The rate with which the data on the internet is growing the need to access this data is becoming a challenge day by day. Natural Language Translating tools significantly reduces the cost of translating of manuals, support content or catalogues. This component of NLP is called as a “Machine translator”.
Automatic summarization: Information overload is a real problem when we need to access a specific, important piece of information from a huge knowledge base. “Automatic summarization” is relevant not only for summarizing the meaning of documents and information, but also for understand the emotional meanings inside the information, An applications of automatic summarization in the Enterprise are media monitoring, newsletters. Financial research, legal contract analysis, social media marketing, question answering and bots, video scripting books and literature etc etc.
Text Classification: Spam filtering is an important application where email messages are classified among two categories, viz. spam and non-spam. NLP component utilised for this scrutiny of spam e-mail is “Text Classification” which makes it possible to assign predefined categories to a document and organize it to help you find the information you need or simplify some activities.
Question Answering: Advancement in speech recognition and understanding creates more need of research in NLP. A “Question Answering”, application is a system capable of coherently answering a human request. It may be used as a text-only interface or as a spoken dialog system. Question answering applications like Siri, Ok Google, Cortana are becoming more and more popular day by day.
So using natural language processing for creating a seamless and interactive interface between humans with machines will continue to be a top priority for today’s and tomorrow’ s increasingly cognitive applications.
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