Information Systems and Computing Technology

Information Systems and Computing Technology, Lei Zhang and Yonggen Gu, Editors, CRC Press, 2013  Contains 23 technical papers from the International Conference on Information Systems and Computing Technology (ISCT 2013, Wuxi, China, 15-16 September 2013). The book reviews recent advances in information systems and computing technology.

These papers are a challenge because after all, Information systems are complex, but included are topics - data collecting, storing, processing and delivery - dear to The Mill Girl's heart.  The main components of current  IT systems are computer hardware and software, telecommunications, databases and data warehouses, human resources, and procedures. But there's more in IT development as innovation technologies and their applications continuously appear, i.e. the Internet of Things (IOT), cloud computing, big data and smart cities.

Two chapters are particularly relevant to manufacturing futurists because they give us a hint of the power and direction data mining and human "imaging" are beginning to have on our integrated IT future.  Plus, the fact that this conference was held in China tells us something about our digital future. 

Take a look at "One shot learning human actions recognition using key poses" to think about how face recognition and body IT can transform security, individualized personal web marketing, and possibly entertainment.  This is another example of what happens when we need to reduce volumes of particulate data to a few meaningful and actionable images.

The second piece that points toward even more individualized human information gathering is "The research of CRM based on a web mining approach".  The initial purpose of web mining was getting, keeping and growing the customer base, better estimation of perforrnance metrics, such as Lifetime Value (LTV), estimating customer responses, collecting and organizing customer data, and building customer profiles and user models.  But how CRM uses data mining and imaging goes beyond these initial very practical forays into understanding what makes people buy, what attracts their interest, what causes them to come together into like-minded and powerful groups.  Because what we want to do now is get, keep and grow the best customers from the start, on purpose, not by accident or price pushes.  Now, according to these experts, the challenge is to understand and develop the model that describes the best lifelong customers, and to go after them, rather than digging and defining the parameters by extracting key data from data mining.  It's a more forward thinking proactive approach that we now can do, predictive analysis.