Researchers from the Palo Alto Research Center (PARC) have developed a software code-named Magitti for the Japanese company Dai Nippon Printing (DNP). When this software is installed on your GPS-enabled mobile phone, Magitti starts to suggest you what to do in your area. You don't need to start a Web search for a restaurant or a movie. Magitti will immediately give you some recommendations based on the time of the day and you past behavior. A deployment is scheduled next year in Japan. But it's unclear if this software will be sold in Europe or in the U.S.
The figure above shows how this recommendation server works. (Credit: PARC/DNP)
Here is how Magitti will work according to Technology Review. "When a person first opens a phone that has Magitti software, she will instantly see a list of recommendations. If it's noon, the software might suggest local restaurants. If it's 3 P.M., it might recommend a nearby boutique for shopping. If it's 9 P.M., a list of pubs might appear. Over time, these recommendations will change as Magitti learns more about the user's behaviors and preferences. The software employs artificial-intelligence algorithms that have traditionally been used in research to make tailored recommendations. If, for instance, a person prefers to eat inexpensive lunches and more-expensive dinners, Magitti will pick up on this (by comparing the GPS location of the restaurant with a database of establishments) and offer up corresponding recommendations."
But Magitti uses other sources of information to refine its suggestions: your messages. "Magitti pulls GPS data from [a user's] phone, as well as text messages and information about events saved in the phone's calendar, and uploads it to a server, along with the user's search terms, says Kurt Partridge, [a researcher at PARC.] Text messages are important bits of information, he notes, because they often include information about future plans. If, for instance, a person is using Magitti to find a restaurant for dinner, and she gets a text message from a friend suggesting sushi, the software will put recommendations for sushi and Japanese restaurants higher on the list.
For more information about this software, you can read a DNP/PARC press release, "DNP, PARC Jointly Develop Recommender System for Mobile Terminals" (September 26, 2007) from which the above figure has been extracted.
You also might want to read an article by Elinor Mills, from CNET News.com, "From PARC, the mobile phone as tour guide" (September 28, 2007), who attended a demonstration of Magitti in downtown Palo Alto. Here is how she describes her experience with the software. "The interface was easy to understand, with large touch-screen 'buttons' that you stroke with your thumb to navigate. The experience is similar to that of the Apple iPhone, but this interface isn't nearly as slick. Another difference is that you can use one hand to operate this system, something many people say you can't do with the iPhone."
And did the software work? "At around 11:30 a.m. Pacific time, the system offered up a host of lunchtime restaurants located nearby, a home furnishings store (in case I felt like shopping) and a gym (in case I felt like sweating). It was easy to expand or limit the distance of suggestions and the type of cuisine, say."
You can see by yourself what Mills discovered by watching this photo gallery (4 pictures).
Of course, this recommendation system is raising some privacy concerns, as reports Technology Review. Victoria Bellotti, a senior researcher at PARC, "says that this is something PARC considered when developing its system. This is why text messages are only kept for a short amount of time. But ultimately, there's a trade-off between privacy and convenience, especially with this new breed of context-aware, location-based technologies. 'I think people will initially accept these location-finding models when there is a big benefit to them,' Bellotti says. 'Once they realize that nothing bad is happening, then they may become even more comfortable with it.'"
Sources: Kate Greene, Technology Review, November 13, 2007; and various websites
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