Washington, Dec 10 (ANI): Want to improve your shopping experience? Well, then here's presenting a system that offers advice on what to buy based on the product barcode and the current weblog buzz around the product.
Takahiron Kawamura and colleagues at Toshiba's Corporate Research and Development Center, in Japan, have developed WOM (word-of-mouth) Scouter to allow shoppers to get the latest reviews for a product they are looking to buy simply while they are in store.
The process involves taking a photo of the item's barcode with a cell phone camera.
The WOM Scouter then looks up the item's meta data via the internet and gathers information from blogs and websites that review the product.
The WOM Scouter than uses natural language processing (NLP) techniques to analyze what blogs it collated are saying about the product and provides a straightforward positive or negative opinion on the product's reputation.
Even the most confused shopper can make an informed decision on that basis, knowing that the blogosphere will support their choice.
The research team has tested WOM Scouter in a consumer electronics store and in a bookstore and suggest that the system represents a case of semantics used to provide an instant bene?t in a mobile computing environment.
In essence, WOM Scouter is one of the first web 3.0 applications that utilises the fundamentals of the original web connectivity, the social media aspects of web 2.0, and provides a service based on the meaning, or semantics, of the data it handles.
The new system could be adapted not only to improve the shopping experience, but to help in choosing a movie to see, a restaurant at which to eat, or potentially whether or not to accept a job offer.
The system has been described in the International Journal of Metadata, Semantics and Ontologies. (ANI)