BEIJING, Nov. 26, 2018 /PRNewswire/ — The 18th IEEE International Conference on Data Mining (ICDM 2018) closed with great success on November 20, 2018, in Singapore. One of the highlights of this year’s conference was the opening keynote speech entitled On Big Wisdom, presented by Prof. Xindong Wu, a world-renowned Data Mining and Artificial Intelligence scholar. During his speech, Prof. Wu introduced a brand-new HAO/BIBLE Framework he co-developed with Minghui Wu, the founder and chairman of MiningLamp Software Systems (Beijing), which defines and illustrates Big Wisdom, and lays the theoretical cornerstone for cutting-edge Industrial Artificial Intelligence.

Prof. Wu was formerly Director of the School of Computing and Information at the University of Louisiana. He is a Fellow of the IEEE and the AAAS. Earlier this year, he joined MiningLamp Software Systems (Beijing) under the invitation of the company founder Minghui Wu, to steer the newly-established MiningLamp Academy of Sciences (MAS) as its President. MiningLamp is a rising industrial AI solutions company in China, and it is known as the Chinese version of Palantir with very promising ambitions. The establishment of MAS is yet another visionary attempt of the company to seek breakthroughs for the applications of industrial AI in China with the help of fundamental research, and the leadership of Prof. Wu brings every prospect of success.

In his keynote speech at ICDM 2018, Prof. Wu defined the HAO/BIBLE framework of Big Wisdom as the integration of human intelligence (HI), artificial intelligence (AI) and organizational/business intelligence (O/BI) with Bigdata analytics in Large Environments; it is a guideline for building industrial intelligence in organizational activities. Big Wisdom starts with Bigdata, discovers Big Knowledge, and facilitates human and machine synergism for complex problem solving. When the HAO/BIBLE framework is applied to a regular (non-Bigdata) environment, it becomes the well-known PEAS agent structure, and when the knowledge graph in HAO/BIBLE relies on domain expertise (rather than Big Knowledge), HAO/BIBLE serves as an expert system.

Prof. Wu also mentioned that under the guidance of HAO/BIBLE framework, MiningLamp and MAS have experimented Big Wisdom for several of MiningLamp’s industry clients in China, including a number of Public Security offices, financial institutions, railway/subway operations companies, government departments in charge of ‘Digital City’ design, etc.

One of the most successful applications is MiningLamp’s public-security knowledge graph, which is a key component of MiningLamp’s latest breakthrough product, the M-Intelligence System 2.0. The MiningLamp public-security knowledge graph is serving more than a hundred provincial/municipal public security bureaus in China, and has currently defined 192 types of entities, 164 types of explicit relationships, 74 types of implicit relationships and 112 types of events; in one of the largest bureaus, it consists of 1.6 billion entities, 4 billion relations, and 14 billion events – the largest existing one of its kind in the industry.

With the help of the public-security knowledge graph and M-Intelligence System 2,0, police officers in China are now able to deal with complicated crime investigations at least 10 times more efficient than before. For instance, a street violence case was reported on May 30, 2017, with the only clue of a picture of the car and the suspect’s figure, and the police officer in charge solved the case in just 5 minutes with only mouse clicking and dragging.

MAS is a fundamental research institution that aims to become an engine for the development of industrial artificial intelligence, and it will serve a wide range of companies beyond MiningLamp in the near future. As a start, Miaozhen Systems, China’s Leading omni-marketing data and technology solution provider, has been applying the HAO/BIBLE framework to their business scenarios of catering services in chain restaurants, and has built a Big Wisdom solution that coordinates the cognitive agents (security cameras, sensors, waiters/waitresses) and action agents (robots and waiters/waitresses for cleaning and food delivery) in chain restaurants for tasks like supply management, personnel deployment, customer-satisfaction optimization, etc. A perfect human-machine synergism with OI and Bigdata is well illustrated in this scenario.

By the end of the speech, as the Steering Committee Chair of ICDM, Prof. Wu announced that ICDM 2019 will come to Beijing. Tsinghua University and MiningLamp will be the co-hosts of ICDM 2019. MiningLamp looks forward to seeing more theoretical and project-landing breakthroughs achieved by the combination of MAS and MiningLamp in the coming year and beyond.

About ICDM

ICDM has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications. ICDM draws researchers, application developers, and practitioners from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases, data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high-quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to advance the state-of-the-art in data mining.

About Prof. Xindong WU

Xindong Wu, President of Mininglamp Academy of Sciences (China), a Yangtze River Scholar at Hefei University of Technology (China), and a Fellow of the IEEE and the AAAS. He holds a PhD in Artificial Intelligence from the University of Edinburgh and Bachelor’s and Master’s degrees in Computer Science from the Hefei University of Technology, China. Dr. Wu’s research interests include data mining, Bigdata analytics, knowledge engineering, and Web systems. He is the 2004 ACM SIGKDD Service Award winner and the 2006 IEEE ICDM Outstanding Service Award winner. He received the 2012 IEEE Computer Society Technical Achievement Award “for pioneering contributions to data mining and applications”, and the 2014 IEEE ICDM 10-Year Highest-Impact Paper Award. He is in charge of BigKE (Knowledge Engineering with Big Data), which is a key project in the National Key R&D Program.

About MiningLamp Software

MiningLamp Software, founded in 2014, is an industrial artificial intelligence solution company which provides automatic analysis and decision-making products and services.

With rich experience in public security, finance, industrial domains, the company focuses on constructing vertical industry knowledge graphs with big data and AI technologies for clients, and is dedicated to realizing AI application by “vertical industry + AI + the revolution of human-machine interaction”, eventually accelerating the transformation from individual intelligence to the entire industrial intelligence.

MiningLamp launched M-Intelligence System as the first Vertical Industrial AI Brain in China in August 2017, and upgraded it to Version 2.0 in September 2018. With secure and reliable operational business environment support, M-Intelligence System 2.0 transfers multivariate & heterogeneous data to industrial knowledge by CONA (an AI-oriented big data governance software product), and stores the vertical industrial knowledge by NEST (a knowledge graph management software product). Then, based on AI technologies such as machine learning, symbolic reasoning, etc., the System realizes real-time computing within seconds and completes online data mining and analysis through SCOPA (an association mining and analysis software product). Step by step, the System builds public security brains, financial risk control brains, industrial safety brains, and humans can interact with the machine brains through natural languages with our enterprise siri “LiteMind”, which makes human-machine interaction as easy as talking to a siri. M-Intelligence System 2.0 provides efficient support for business decision-making, and increases the efficiency of transforming data and knowledge into enterprise competitiveness.

SOURCE MiningLamp Software