Reading this Technology Review, it seems inevitable that such advanced mining technologies will pop-up in the near future. The world has a wealth of information and every single thing will be data mined in the future. And what a movement that will be.
By the way, the MIT Technology Review calls Reality Mining as one of the 10 technologies that we think are most likely to change the way we live. Exciting, Ain’t it ?
Also Surprise Modeling which combines data mining and machine learning to help people do a better job of anticipating and coping with unusual events is also one of the Top 10 Technologies listed by MIT Tech Review. This is being advocated by Eric Horvitz, Microsoft Research.
From the article on Reality Mining -
Reality mining, he says, “is all about paying attention to patterns in life and using that information to help [with] things like setting privacy patterns, sharing things with people, notifying people–basically, to help you live your life.”
Within the next few years, Pentland predicts, reality mining will become more common, thanks in part to the proliferation and increasing sophistication of cell phones. Many handheld devices now have the processing power of low-end desktop computers, and they can also collect more varied data, thanks to devices such as GPS chips that track location. And researchers such as Pentland are getting better at making sense of all that information.
To create an accurate model of a person’s social network, for example, Pentland’s team combines a phone’s call logs with information about its proximity to other people’s devices, which is continuously collected by Bluetooth sensors. With the help of factor analysis, a statistical technique commonly used in the social sciences to explain correlations among multiple variables, the team identifies patterns in the data and translates them into maps of social relationships. Such maps could be used, for instance, to accurately categorize the people in your address book as friends, family members, acquaintances, or coworkers. In turn, this information could be used to automatically establish privacy settings–for instance, allowing only your family to view your schedule. With location data added in, the phone could predict when you would be near someone in your network. In a paper published last May, Pentland and his group showed that cell-phone data enabled them to accurately model the social networks of about 100 MIT students and professors. They could also precisely predict where subjects would meet with members of their networks on any given day of the week.