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Dr. Wei Cui, Chief Scientist of Squirrel AI Learning of Yixue Education, Serves as Local Chair of ACM CIKM 2019 Conference to Explore the Application Practices of AI in the Field of Education

November 29, 2019 GMT
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Dr. Wei Cui, Co-founder and Chief Scientist of Squirrel AI Learning and Local Chair of ACM CIKM 2019, Delivered a Speech
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Dr. Wei Cui, Co-founder and Chief Scientist of Squirrel AI Learning and Local Chair of ACM CIKM 2019, Delivered a Speech

BEIJING, Nov. 29, 2019 /PRNewswire/ -- Recently, ACM CIKM 2019, an international top event for information retrieval and data mining, was held in Beijing. As a world-renowned technology summit, this session took “AI for Future Life” as the theme, demonstrated the next generation technologies from the fields of AI and big data, and explored the critical role of AI technologies based on deep learning in the fields of information retrieval and data mining, which attracted nearly 1,000 experts and scholars from all over the world.

It is worth noting that ACM CIKM 2019 is the 28th session of CIKM and the second time CIKM has come to China since it was first held in 1992. The event gathered many big names. Academician Hong Mei and Ramamohanarao Kotagiri served as the Honorary Chairmen of the conference; Professor Wenwu Zhu and Professor Dacheng Tao served as the Chairmen of the conference; Dr. Wei Cui, the Co-founder and Chief Scientist of Squirrel AI Learning served as the Regional Chairman of the conference, bringing a brilliant sharing of application practice to everyone.

Data mining is the advancement of data analysis, while AI is the extension of business intelligence. In this conference, in addition to Dr. Wei Cui, famous scholar Steve Maybank, Jiawei Han, Jian Pei and Jianping Shi also respectively delivered keynote speeches to explore the development trend of technology. In addition to the necessary tutorial, workshop, oral and poster presentations for the summit, this conference also held the AnalytiCup and more than ten industrial plenary speeches.

Encounter on the Same Field to Explore the In-depth Application of AI Technology

“We believe that in the future, AI will penetrate into all aspects of life. At present, it is mainly applied to deep learning. However, this conference hopes to discuss what kind of development trend will be in the future for deep learning and traditional statistical learning.”

As an internationally renowned scholar in the field of AI and information science, Dr. Dacheng Tao, General Chair of the conference, said at the beginning of the conference that many advanced technologies have been understood and mastered by the Chinese people, and even breakthroughs have been made. Under the current trend of science and technology, it is particularly important to explore the in-depth application of new technologies.

Dr. Wei Cui, Co-founder and Chief Scientist of Squirrel AI Learning, also fully agrees with this. As the first company that has developed the AI adaptive learning engine with complete independent intellectual property rights and advanced algorithm as the core, Squirrel AI Learning has used a variety of AI technologies such as evolutionary algorithm, neural network technology, machine learning, graph theory and Bayesian Network to recommend personalized learning solutions to students in the past few years of practice. The further in-depth application of technologies and the real-time improvement and update of products are closely related to the education status and future of hundreds of millions of students.

At the event, Prof. Jiawei Han, Professor of the Department of Computer Science at the University of Illinois Urbana Champaign, ACM and IEEE Fellow, Director of the American Information Network Academic Research Center, Prof. Steve Maybank, Professor of the Department of Computer Science at the Birkbeck College, University of London, Academician of the European Academy of Sciences and IEEE Fellow, and Wenwu Zhu, Deputy Director of the Department of Computer Science at Tsinghua University, and Deputy Director of the National Research Center for Information Science and Technology and other experts and scholars shared their insights in the field of AI technology with Dr. Wei Cui, the Co-founder and Chief Scientist of Squirrel AI Learning, reflecting the latest research trends in technology.

For example, Professor Jiawei Han noted that it is still a long way to transform real data to structured data and then to useful knowledge. “In order to transform the existing unstructured big data into useful knowledge, the first thing to do is to structure the data. He proposed two forms of structured data, one is Heterogeneous Network, and the other is Multi-dimensional Text Cube. Knowledge generated from this structured data has proven to be very powerful, but it is very difficult to transform the original unstructured data into structured data (Network or Text Cube).”

According to Professor Han, a large number of text data itself implies a large number of hidden patterns, structures and knowledge, and therefore we can use the domain-independent and domain-dependent knowledge base to explore how to transform massive data from unstructured data into useful knowledge. “On this road, we have only found a few openings to go forward. Now it is not a road yet, but just a small path. If we want it to be a broad road, we need to work together. As long as this road is wide, we can transform a large number of unstructured texts into a lot of useful knowledge in the future.”

Realize Breakthroughs and Solve the Difficulties in Traditional Education with AI

From industrial production, to family life, and then to voice assistants on various electronic devices, AI and robotics are rapidly transforming this era that belongs to us. For many years, the shortage of senior teacher resources and geographical problems in China’s education have affected the popularization of high quality education. But now, AI technology is penetrating into our lives so as to solve the difficulties in traditional education.

Specifically speaking, the intelligent adaptive learning system of Squirrel AI Learning is a student-centered intelligent and personalized education. It applies AI technology to the processes of teaching, learning, assessment, testing and training, to achieve the purpose of surpassing human teaching on the basis of simulating excellent teachers. With high cost performance, the product adopts the mode of AI + human teachers to teach students according to their aptitude, which can effectively solve the problems of high class cost, limited famous teacher resources and low learning efficiency of traditional education.

In his speech, Dr. Wei Cui introduced the basic techniques used to build the system and performance assessment experiments. Squirrel AI’s intelligent adaptive learning engine consists of a three-layer architecture: ontology layer, algorithm layer and interactive system.

The ontology layer mainly focuses on content, including a learning map and a knowledge map. Squirrel AI Learning can split the knowledge points in the discipline into super-nano-level knowledge points, so as to have a clearer understanding on the mastery of knowledge points by students. It can accurately detect the weak points of children’s knowledge, and accurately give the most suitable learning path for each child, so as to improve his/her learning efficiency. Taking junior high school mathematics as an example, Squirrel AI Learning can refine 3,000 knowledge points into 30,000.

The algorithm layer includes a content recommendation engine, a student user portrait engine and a target management engine, etc. Squirrel AI Learning will combine the user state assessment engine and knowledge recommendation engine to build a data model, so as to accurately and efficiently detect each student’s knowledge loopholes, and recommend corresponding learning content according to the loopholes.

The interactive system is used to learn more about students’ information by collecting interactive data and perfect the algorithm. The MIBA multimodal comprehensive behavioral analysis AI system developed by the Squirrel AI Learning and the Stanford Research Institute can detect students’ login time, learning time, speed and results, and capture the children’s real-time data, such as eye movements, brain waves and other comprehensive values through monitoring to judge the concentration and focus of students’ learning, so as to judge the learning content of the next link.

In addition, the MCM system of Squirrel AI Learning can detect people’s model of thinking, learning capacity and learning method. After the assessment and detection, MCM system can analyze different learning capacities, learning speeds, blind spots and weak spots of knowledge points for those learners with the same score, so as to accurately depict the user portrait of learners.

“Compared with the rapid development of Internet technology and AI technology, in fact, our education field is developing very slowly.” Dr. Wei Cui pointed out that Squirrel AI Learning is solving the difficulties in traditional education. In the past four years, Squirrel AI Learning has opened more than 2,300 learning centers in more than 700 cities and counties in more than 20 provinces across the country, providing high quality teaching services to nearly 2 million students.

“In the future, we will further strengthen our product technology research and development capabilities, join hands with more experts in adaptive learning to enhance the intelligent adaptive learning system to a higher level.”

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SOURCE Squirrel AI Learning