The document discusses advanced natural language processing (NLP) techniques, including named entity recognition, sentiment analysis, and semantic search, which guide modern data mining efforts. It highlights the capabilities of Repustate's sentiment analysis API, which utilizes these techniques across various media formats without translation, providing advanced multilingual support. The platform is designed to improve data understanding for brands, addressing complexities of social media and enhancing productivity.

2. Advanced NLP techniques
that guide modern data
mining
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3. Table of Content
● What Is Natural Language Processing (NLP)?
● What Are Top Advanced NLP Techniques?
● Leverage NLP Technology With Repustate

4. Overview
Advanced NLP techniques like named entity recognition (NER),
semantic search, text summarizations, sentiment analysis, are top
NLP technology tasks that guide the modern data mining industry.
In this article we will take a look at these and other important NLP
techniques including aspect-based granularity, machine
translations and more.

5. What Is Natural Language
Processing (NLP)?
Natural language processing (NLP) is a sub-task of artificial
intelligence that analyzes human language comprising text and
speech through computational linguistics. It uses machine learning
and deep learning models to understand the intent behind words in
order to know the sentiment of the text. NLP is used in speech
recognition, voice operated GPS phone and automotive systems,
smart home digital assistants, video subtitles, sentiment analysis,
image recognition, and more.

6. What Are Top Advanced NLP Techniques?

8. Leverage NLP Technology With Repustate

9. A sentiment analysis API uses almost all of the advanced NLP techniques
mentioned above and more, to help brands find the information they need to
increase their productivity and return on investment. Repustate’s has all-in-one
sentiment analysis dashboard, Repustate IQ, uses natural language processing
and machine learning to process data in all formats - video, audio, text, and
images - to give the most accurate results. Its multilingual capability stems from
part-of-speech taggers that are uniquely built for each of the 23 languages it
supports. Repustate IQ does not use translations to convert one language into
another for the purpose of analysis, but rather reads the data natively.
Furthermore, its NER capability is highly advanced and extremely rich, supporting
all major industries including retail, government, banking, automotive, hospitality,
finance, and others. The platform reads social media listening data seamlessly
and as easily as it does video or document thanks to advanced NLP techniques.
The solution understands all the complexities of social media such as
abbreviations, special characters, hashtags, code switches, emojis, and

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