Mobile Data Mining

In recent years, with the emergence of new forms of information, represented by social networking sites, location-based services, and the rapid development of cloud computing, mobile and IoT technologies, ubiquitous mobile, wireless sensors and other devices are generating data at all times, Hundreds of millions of users of Internet services are always generating data interaction, the big Data era has come. In the present, large data is hot, whether it is business or individuals are talking about or engaged in large data-related topics and business, we create large data is also surrounded by the big data age. Although the market prospect of big data makes people ...

Keynote speaker: Xionghui Moderator: Carey: Zhongguancun Large Data Industry Alliance Mr. Xionghui is the associate dean of the Department of Management Science and information systems at Rutgers-New Jersey State University in the United States, a tenured professor. The main areas of research include: data mining, large data, business intelligence, mobile computing, and information security. Obtained the highest academic award at the University of Rochester in 2009. He was also invited to participate in the organization of international top-level meetings (such as KDD, ICDM,ICML,ICDE and SDM) and as a member/chair of the International Conference Organizing Committee. He is also currently serving as IEEE ...

Keynote speaker: Xionghui Moderator: Carey: Zhongguancun Large Data Industry Alliance Mr. Xionghui is the associate dean of the Department of Management Science and information systems at Rutgers-New Jersey State University in the United States, a tenured professor. The main areas of research include: data mining, large data, business intelligence, mobile computing, and information security. Obtained the highest academic award at the University of Rochester in 2009. He was also invited to participate in the organization of international top-level meetings (such as KDD, ICDM,ICML,ICDE and SDM) and as a member/chair of the International Conference Organizing Committee. He is also currently serving as IEEE ...

I'm a novice in data mining and machine learning, starting with Amazon last July, and because of the need for passive contact with work that has never been contacted before and what is needed to predict machine learning. Later, to Taobao, their own initiative to do a few months and user address related data mining work, there are some superficial experience. 　　Anyway, welcome advice and discussion. In addition, note that the title of this article imitates an American drama "Game of Thrones: The Song of Ice and Fire". In the world of data, we see a lot of cattle, very strong ...

With the development of telecom industry, the competition among telecom operators has become fiercer. In order to win in the competition, the right business strategy becomes the key link of the telecom operator's success. Telecom operators have a large number of user data information, using data mining technology, can be in billing data, business order data, network management data, such as the mass user data found business knowledge, for the market to lay the foundation for precision marketing. With the expansion of China Mobile users and the diverse demands of application targets, data mining applications face new challenges. First of all, the user size is growing, by a large number of users produced a huge amount of data, including ...

After the arrogant data has entered the people's view, it gradually becomes the focus that people pay attention to generally. Large data is the PB era of science, in essence, the challenge of large data is the PB era of science challenges, but also the cognitive science including data mining challenges. 　　So what about data mining in the big data age? In modern times, people often say that large data mainly includes three sources: the first is the large data of nature, the natural environment on Earth, very big. The second is the big data of life. The third and most important is the social data that people care about. These data are common ...

Now Big data fire is not good, almost everyone is talking big data, but what is big data, I am afraid not how many people know, weeding too many people. 　　Big data doesn't mean a lot of data. So not storing a lot of data is in the big data, because "big data" is simply a short name, said that the whole point should be "http://www.aliyun.com/zixun/aggregation/14185.html" > Large data Mining, The big data that hasn't been dug up is just the original ...

In the big data age, the data is changing our thinking. There are a few pictures to let us see, the first picture, published in July 2013, a number of Chinese Internet, the second is the proportion of Chinese mobile internet users, I think we should pay attention to the growth rate of mobile phone is very high. At the same time to share with you a data, Archie in the mobile end of the layout is relatively early, we started in 2011 to predict when the mobile end of the flow will exceed the PC side. We originally had a forecast at the end of 2013, but after actual operation, actually in 2013 of 9 ...

With the rapid development of mobile internet, mobile shopping is gradually being paid more attention in the market. 　　The industry is also widely predicted that in 2012, with the rapid and rapid development of the market-oriented smartphone, the new electric quotient environment will accelerate the innovation of the electric business with the characteristics of random and time fragmentation. According to emarketer, a market research group, 50% of Americans now have smartphones. Experts also predict that by 2015, 8% of E-commerce transactions will be completed via mobile platforms. China's mobile-phone boom is also not comparable, from the Apple 4S crazy hot ...

Data mining, which mainly solves four kinds of problems, is a very clear definition of several kinds of problems that it can solve. This is a high degree of induction, and the application of data mining is a process to deduce these types of problems. So let's look at how the four types of problems it solves are defined: 1, classification problem classification problem is a predictive problem, but it is different from the general prediction problem, but the difference is that the results of its predictions are categories (such as a, B, C three) rather than a specific value (such as 55, 65, 75 ...). ...)。 ...