Other interesting books:
Software in mobile phones is becoming more and more complex. Errors and bugs express this complexity. Fortunately, we can now update the software, correct the problems and in some cases add functionalities. Not for all models but the latest Nokia mobile phones offer this possibility.
Google scholar is a great tool to find scientific publications.
However, Google also offers lectures given in their labs about many and various interesting topics to a wider audience.
It is possible to see these videos from Google Video.
Data mining is the art of extracting “useful” information from data, usually a lot of data. If we could access, extract and make sense of information from:
- calendar events
- social network (friends)
- what emails we write, to whom and how often
- what information we look for in the Internet
- what books we read
- which rss feeds we read
we would have a quite accurate profile of a person. The fact is that this analysis is constantly done by all major search engines and not only by them. Every advertiser is trying to understand users´ habits. The scope is to understand better us in order to offer targeted services, services we (probably) like and want. Actually, the idea is sound. However, concerns regarding our privacy are legitimate. The big brother in 1984 by Orwell is a classic when we discuss about privacy concerns. A more recent book is Data Base Nation by Simon Garfinkel. This latest book is a great book and a good read. Still, it does not represent the curren situation since it was written when search engines were not as “powerful” as we see today.
At the moment, user location is not used, or at least, not yet…
A video worth a view
Yes, it is possible to predict what you are going to do next.
It is a fact that we all have a quite predictable life. 5 days a week we go to work, and we spend there more or less the same number of hours. At a certain time we have lunch and in the evening we have dinner. Well, using this information is possible to develop services which predict what we will do next and eventually provide help or suggestions.
Adrian Flanagan, a collegue of mine, has developed an algorithm that does just that. The paper title is Unsupervised clustering of context data and learning user requirements for a mobile device.
The great feature of this approach is that it does not need to be trained beforehand but it learns as it is used.
For example, by adding the following PHP code in a web page we can extract the IP, Operating System, Browser type, and HTTP Referer:
echo “Your remote address: “;
echo “Your browser, operating system, language settings: “;
echo “coming directly to this webpage”;
else echo “Coming to this page from: “.$_SERVER[‘HTTP_REFERER’];
Using the IP address we can deduce, country, city, and sometimes from which organization the visitors are coming from, e.g. University XX. Tools such as the Unix commands whois, host, nslookup are useful. Additionally, several websites offer geocoding services. Use a Google search to find them out.
document.write(“screen resolution: “)
document.write(screen.width + “x” + screen.height+”, “)
document.write(“Color Depth: “+screen.colorDepth+ “, “)
document.write(“Java Enabled: “+ navigator.javaEnabled())
And we can also learn whether they came to our webpage using a search engine and which keywords they used . The following script provides an example, copy&paste it to your home page: extract search engine keywords