Instore web 3.0 scouting

Dec 09, 2008

Scientists at Toshiba's Corporate Research and Development Center, in Japan have developed a system that offers shoppers advice on what to buy based on the product barcode and the current weblog buzz around the gadget. The team describes the system WOM Scouter this month in the International Journal of Metadata, Semantics and Ontologies.

If you've ever been at the mall hoping to choose, the latest mp3 player, camera, high-definition TV, you know how confusing the huge array of choice can be. You only have the sales assistant's word for whether a particular brand or model has a good reputation. Checking each and every model while in the store would be almost impossible, without a lot of mobile web browsing and manually entering model numbers into search engines.

Now, Takahiron Kawamura and colleagues 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 Toshiba team has tested WOM Scouter in a consumer electronics store and in a book store and suggest that the system represents a case of semantics used to provide an instant benefit 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.

WOM Scouter 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.

Source: Inderscience Publishers

Explore further: New algorithm identifies data subsets that will yield the most reliable predictions

add to favorites email to friend print save as pdf

Related Stories

Google made failed bid for Spotify

3 hours ago

Internet titan Google tried last year to buy streaming music service Spotify but backed off for reasons including a whopping price tag, the Wall Street Journal reported on Tuesday.

Thieves got into 1K StubHub accounts

4 hours ago

(AP)—Cyber thieves got into more than 1,000 StubHub customers' accounts and fraudulently bought tickets for events through the online ticket reseller, a law enforcement official and the company said Tuesday.

Microsoft CEO sees 'bold' plan as 4Q tops Street

4 hours ago

(AP)—Microsoft Corp. CEO Satya Nadella painted an upbeat vision of the future Tuesday, saying that the next version of Windows will be unified across screens of all sizes and that two money-losing units—Nokia ...

Recommended for you

Designing exascale computers

Jul 23, 2014

"Imagine a heart surgeon operating to repair a blocked coronary artery. Someday soon, the surgeon might run a detailed computer simulation of blood flowing through the patient's arteries, showing how millions ...

User comments : 0