Welcome to YouNet AI Website

Transforming Enterprises with Artificial Intelligence

Who We Are

Key members of the ai.younetgroup.com

Tho Quan

Scientific Advisor

PhD. in Computer Science (Nanyang Technological University, Singapore.
Vice Dean, Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology.
Expert in Natural Language Processing and Data Mining

Minh Truong

Technical Architect

Mr. Minh Truong received his B.Eng. degree in Computer Science from Ho Chi Minh City University of Technology in 2012. He won VEF fellowship in 2014 to study at Iowa State University, USA, and completed his Master degree in 2016 under the supervision of Prof. Srikanta Tirthapura. His primary focuses now are on natural language processing and large-scale distributed system based on Hadoop.

What We Do

The ultimate goal of ai.younetgroup.com is to make AI-powered end-to-end products. We aim to be No 1 AI company in SEA, specialized in Natural Language and Image Processing for MarTech. Currently, our focus is targeted to NLP areas first.

Our AI products meet state-of-the-art performance, battle-tested and backed by a strong AI team. Our sentiment analysis, being open for public usage, has enjoyed the accuracy of 85%. Our influencer tools are more trustworthy in Vietnamese market because we invested a lot to understand the Vietnamese text. Other competed companies will not have this advantage, at least for next 3-5 years, as our AI technology has already surpassed them in our languages and our niche domains


Our sentiment engine can precisely tell if a Vietnamese text is Positive, Negative or Neutral. Apart from using state-of-the-art AI techniques such as word and character embedding, densed connection of BiGRU and CNN layers, we will improve the ability to analyze sentiment based on context, domain and object detections. In addition, we also support Vietnamese diacritic and basic NLP analysis such as POS, NER etc. One can try our demo at http://ai.younetgroup.com/demo


We develop chatbot tailored for domains like banking, entertainment, FMCG, etc. Currently we already have a working version for real estate, and developing a new solution for retailer. Some applications of this tool include reducing the burden of human by automating some initial chat experience before handing to human, support comparing, extract information, enhance customer experience on existing websites. Our first prototype can be accessed via http://ai.younetgroup.com/demo


Text classifier We also developed a general text classifier with hundred of unique labels for wide range of categories from sport, entertainment to education, porn, inappropriate. Some notable applications include sentiment and spam rating, influencer classification, customer segmentation and comment categorization.
Topic Modeling Topic modeling implies detecting topics from a set of documents. Latent Dirichlet Allocation (LDA) is a well-known approach for this task. However, this approach suffers from poor performance when handling short text commonly occurring in social media. By combining LDA and emerging NLP approaches of word vectors and deep learning, we successfully modeled topics from a vast dataset of short textual mentions. Our results are being applied to real products for calculating resonance scores of influencers or classifying spam messages.

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