Data-Tag is a Natural Language Processing based Text Classification system, which utilizes Open Data from Wikipedia along with Word-Sense Disambiguation algorithm to find semantic similarity and outputs tags accordingly.

What problem does it solve?

• Provides an alternative for keyword based classifications
• Tags data according to their semantic meaning
• Makes text classifiers more artificially intelligent

What's new in Data-Tag?

• Semantic Nature
• Uses Wikipedia Data as gloss for finding semantic similarity
• Can tag textual as well as data from web pages
• extends capability of WSD to multiple classes
• No Database requirements - using existing data from internet

User Interface/Demo

Technologies/Frameworks Used

• Python - Flask
• JavaScript - AngularJS
• Natural Language Toolkit
• Wikipedia API
• Redis - noSQL Database
• Pattern Framework
• grrequests
• urllib3

Sequence Flow

• Send data from Angular Controller to Flask Back-end
• Tokenize text
• Apply Part-of-Speech Tagging
• Extract Nouns
• Get pages from Wikipedia based on extracted nouns
• Apply Word Sense Disambiguation
• Get matching scores
• Return top 3 tags with highest scores

Sequence Diagram

Shortcomings

• Slower processing on Slower networks
• may provide inaccurate results for larger number of tags
• No Memoization 
• Supports only "English" language

Scope/Future Work

• Can be incorporated with a web crawler for semantically tagging web pages
• Can be used with Machine learning techniques to provide more accurate results
• May acts as a basis for NLP Query Formulation from web data

Conclusion

Systems like Data-Tag are the future of semantic text over internet. It aims in dropping age-old keyword based classification systems and welcomes the advent of more Artificially Intelligent systems. It further provides a basic structure to develop larger systems utilizing the similar concepts to classify data all over  the internet and textual documents.

Thank you.