Content Is King -- Even Better When It's Free

How many times have you heard that phrase, "Content is king." If you are a blogger like me, you hear it a lot. It becomes an unending drumbeat, pushing you back to your keyboard to update your site to grab more visitors, page views, etc.

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This was a sponsored post.

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Toshiba Scientists Offer New Tool For Consumers

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 blog 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.

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Carnegie Mellon Algorithm Identifies Top 100 Blogs For News

Being among the first to pick up on Internet news and gossip and rapidly detecting contamination anywhere in a water supply system are similar problems, at least from a computer scientist’s point of view. Both can be solved with a versatile algorithm developed by Carnegie Mellon University researchers.

Using a problem-solving method called the Cascades algorithm, Carlos Guestrin, assistant professor of computer science and machine learning, and his students compiled a list of the best 100 blogs to read to find the biggest news on the Web as early as possible. It includes well-known blogs, such as Instapundit and Boing Boing, but also some more obscure ones like Watcher of Weasels and Don Surber.

“The goal of our system when looking at blogs is to detect the big stories as early on and as close to the source as possible,” Guestrin said. He, Andreas Krause and Jure Leskovec, doctoral students in computer science and machine learning, respectively, analyzed 45,000 blogs (those that actively link to other blogs) to compile the list, checking the time stamps to determine where news items were being posted first.

But reading even 100 blogs, many of them with numerous postings, may be more than many Web surfers can handle. Recasting the problem, the researchers used their algorithm to compile a list of blogs if a person wanted to read only 5,000 postings. This list is quite different, with “summarizer” blogs, such as The Modulator and Anglican predominating.

Similarly, Guestrin and his students used the same algorithm to determine the optimal number and placement of sensors for detecting the introduction and spread of contaminants in a municipal water supply. Their report on the blog and water system case studies, “Cost-Effective Outbreak Detection in Networks,” was presented at the Association for Computing Machinery’s International Conference on Knowledge Discovery and Data Mining earlier this year.

“Nothing demonstrates the versatility of Carlos’ algorithm better than its ability to solve these two difficult and seemingly different problems,” says Randal Bryant, dean of Carnegie Mellon’s School of Computer Science. “It’s a credit to Carlos’ insight and inventiveness, but also a testament to the power of computational thinking. Computer scientists increasingly are developing common methods for solving problems that apply across any number of disciplines.”

Guestrin began work on the Cascades algorithm in 2004 to find a way to balance the cost of collecting information with the need for collecting the information early and close to its source. Initially, this addressed problems in designing wireless sensor networks — a technology that potentially can monitor such important conditions as water quality, building temperature, vital signs of nursing home residents, algal blooms in lakes and the structural integrity of bridges. In all of these cases, deploying the wrong number of sensors or putting them in the wrong places wastes money and produces poor information.

The algorithm allows for near-optimal placement of sensors by exploiting a property called submodularity. Simply put, submodularity means there is a diminishing return associated with adding sensors — adding a sensor to a five-sensor network has much more impact than adding a sensor to a 10,000-sensor network. The algorithm also takes into account the property of locality — the idea that sensors that are far apart provide almost independent information.

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Video: Recap of Blogger Confab

James Taranto of OpinionJournal.com recaps the antics at the Yearly Kos blog confab in Chicago. The event also attracted the leading Democratic presidential candidates, including Sen. Hillary Clinton of New York.

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Video: Interview With Technorati Vice President

Technorati is at the heart of that fabled place, the "Blogosphere."

Based in San Francisco and founded by David Sifry, Technorati is the Google of the blogs, performing as a search engine for more than 75 million weblogs, according to one estimate.

Today Technorati finds itself competing with Google and Yahoo for blog search.

Watch this interview with Derek Gordon, vice president of marketing at Technorati:

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