An IBM Company

Case Study Tabelog

Tabelog Spices Up Virtual Restaurant Experiences with Image Analysis

Wondering where you should go for a meal to remember? If you do not have a place already in mind, finding the right dish to satisfy your craving can be hit-or-miss.

Tabelog is taking the guesswork out of the situation by combining reviews, food photos and guest blogs in an online directory and review service that helps you discover the best dining experiences in foodie-centric cities across the U.S. Like other directories, reviews are posted on the site daily. But what makes it unique are featured food bloggers and the images those bloggers post via SMS. Tabelog also pulls images from social media and then analyzes them to ensure you get an accurate, reliable sense for what you can expect as well.

Tabelog was developed by Takehiro Miyajima and his team, including American expat Matthew Pinkston, at the Kakaku.com Group. Headquartered in Japan, they have experienced a great deal of success with a more extensive online directory (kakaku.com). Based on the popularity of Kakaku’s restaurant section, the company decided to launch a similar directory in the United States.

The Challenge: Finding Images That Help Foodies Virtually Experience RestaurantsEvery day, Tabelog collects over 1,000 restaurant and food relevant photos from Foursquare and Instagram that can be used in their directory. However, a large portion of those images are selfies or group photos that do not convey any useful information about the food or restaurant experience. For Tabelog’s directory to serve its purpose – virtually recreating a specific restaurant experience – the application driving the directory filters those images to find appropriate and informative photos.

Images present a complex unstructured data analysis challenge. While there is no shortage of imagery on the Web, the extensive depth of nuance and abstraction makes “understanding” what the image represents more difficult than text, which comparatively has a much more finite pool of potential meanings associated with each word.

Pinkston says that the primary challenge he faced was achieving high image analysis accuracy. Ultimately, providing meaningful images along with the reviews

Company Profile:•Web directory/review service

NLP Problems:• Accuracy in image recognition• Integration with Instagram and Foursquare• Limited development resources

AlchemyAPIs Used:• Image Analysis

Volume of Content Analyzed:• 1,000+ photos/day analyzed• 40,000 users interacting with site daily• 100,000+ registered restaurants

Type of Data Analyzed:• Images•Photos

Result:•Tabelog.us, a “specialized social networking site”•Viral adoption by restaurants and users•Rapid application and site development

An IBM Company

Case Study Tabelog

is essential to building trust with site users and the restaurants that are registered there. “We started by using a CV (computer visualization) library to do facial analysis and then throw out pictures that contained faces. While that was a good service, it did not give us the accuracy we needed, sometimes allowing blurry or random images through, like a poster or brick wall. We needed to take it to the next level of precision.”

The second challenge was integrating with Instagram and Foursquare, the sites that provide the imagery and location data. Pinkston’s team sought a language agnostic, REST API to make the connection quick and stable.

Development with limited engineering resources was also a big hurdle. “We have a small team of engineers,” Pinkston says, “So the ability to call photo-sharing, geo-location and image analysis services rather than developing those functions ourselves is essential.”

The Solution: Image Analysis REST API That Finds the Best Images to Represent a RestaurantAfter researching and evaluating a couple of photo analysis services, Pinkston discovered AlchemyAPI. “As an experienced developer, one of the first things that impressed me was how quickly I implemented the Image Analysis API,” he remarks. “It only took an hour to get a custom library built and working with it. Also, the simplicity of the REST API makes it language agnostic and gives us the cross-domain integration we need.” The other factors that convinced him to use AlchemyAPI are performance-based; competitive services did not reliably filter images like they wanted.

Part of building the solution included working with the AlchemyAPI team to adjust the API settings to align with the volume of calls Tabelog executes, an unforeseen complication. “There are always little ‘hiccups’ when integrating with external services, and our site does that heavily,” Pinkston explains. “We were able to work through the issue after just a few email exchanges.”

The result is Tabelog.us, which Pinkston describes as “a very specialized version of social networking.” The tagline on the Tabelog homepage is: “A lively online community for foodies, by foodies.” The key idea being “lively,” since the content constantly changes. Professional food bloggers, food photographers and site visitors write reviews that update and enrich the site every day.

The Value: Increased Productivity, Dramatic Time Savings, Desired ResultsFrom Pinkston’s perspective, “AlchemyAPI’s services dramatically reduce the amount of time that a person would otherwise need to spend on the mundane and

“AlchemyAPI’s services dramatically reduce the amount of time that a person would otherwise need to spend on the mundane and repetitive task of separating truly useful images from mountains of unrelated or even inappropriate content. We can now dedicate those hours to more productive, interactive and interesting tasks.”

Matthew Pinkston,Tabelog

An IBM Company

Case Study Tabelog

repetitive task of separating truly useful images from mountains of unrelated or even inappropriate content. We can now dedicate those hours to more productive, interactive and interesting tasks.”

The value extends to Tabelog’s customers as well. Over 40,000 foodies visit the site, confident that Tabelog will provide accurate and reliable recommendations. Additionally, more than 200,000 registered restaurants use the site to help brand and promote their establishment. With Tabelog, restaurants reach their target audience and people around the U.S. can find new adventures in dining.

ConclusionConsidering the tremendous volume of data posted on social sites, a service that enables making informed decisions can not only save visitors time, but money. With AlchemyAPI’s Image Analysis service, Tabelog rapidly eliminates irrelevant and inappropriate content to make your experience on the site and at the restaurant you choose equally enjoyable.

What does Pinkston think the future of Tabelog looks like? More automation, more integration with other food blogs and, as a result of a more extensive knowledge base of image analysis results to draw on, an even better taste of what to expect when deciding where to go for a meal.

About AlchemyAPIAlchemyAPI’s mission is to power a new generation of smart applications that understand human language and vision by democratizing breakthroughs in deep learning-based artificial intelligence. Our easy-to-use, high-performance cloud services for real time text analysis and computer vision give companies the intelligence needed to transform vast amounts of unstructured data into actions that drive their business. AlchemyLanguage™ is the world’s most popular natural language processing service; AlchemyVision™ is the world’s first computer vision service for understanding complex scenes. AlchemyAPI is used by more than 40,000 developers across 36 countries and a wide variety of industries to process over 3 billion texts and images every month. For more information, visit our website at www.alchemyapi.com.

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