Integrating Natural Language Processing with Your Mobile Apps
Generation of keywords
NLP helps in generating keywords and applying an AutoTag to know the subject available in the text.
Summation of the text
In the application, while calculating the text to identify precious ideas, NLP text summation is helpful.
The building of chatbots is done by the Parsey McParseface with tags Point of the Speech.
To discover a person in the form of identifying an entity, an organization uses the Named Entity Recognition of NLP.
For words reduction to the stems by applying Porter Stemmer or to divide the text into tokens by using a Tokenize, NLP helps with its valuable feature.
It is specially used for recognition of the sentiment of the text. And even can vary from neutral to bad or good.
Deep Learning Using Statistical Algorithms Now Possible in Mobile
Full-Cycle NLP Application
We intensely analyze the requirements of your application and assist you in formatting the scope of work with a detailed development phase, including its cost and time.
For semi-structured data to be classified, our engineers work on web sources using standard methodologies.
With State-of-the-art development practices along with industry-standard tools for best architecture, our team strives to deliver a seamless, integrated application.
It contains data possession and processing to analytics, content categorization, content clustering, entity extraction, relationship extraction, and fact extraction.