Edamam

Originally, the web site app mirrored the mobile versions. But, says co-founder and CEO Victor Penev, “We realized that people wanted to be able to access recipes and search on the desktop, and they should have a holistic experience from anywhere.” While the company had been more focused on the mobile arena, Penev says building traffic for the website is going to be a priority too. Among the capabilities users should see in the near future are functions like one that will let people save recipes on their iPhone or Android mobile devices and then access them on their iPads or desktops, or vice verse.

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Semantic technology is helping the company reach its goal. “A big problem is that data about food is very messy,” says Penev. “It’s hard to find something, what you find often contradicts other information of what is good for you and what the calories are. So we set out to solve that problem. We played around with different approaches but settled on using semantic technology.”

The confusion arises in part from the fact that recipe sites themselves usually just hire services to calculate nutritional data. But that may lead to mistakes when calculations aren’t undertaken with exactitude — substituting white cream for heavy cream nutritional details changes the whole profile of the recipe, he says.

So, what is that right semantic stuff? One piece of it is that, in conjunction with Ontotext, Edamam built a food ontology. An ontology can be the foundation for a lot of things, such as extracting the knowledge of the chemical composition of a particular recipe and thus inferring its flavor and texture. And Edamam means to grow its own to include various datasets such as chemical data (for flavor and texture), geolocation (for local and seasonal recipes), product data (for e-commerce). and more.

But initially, it’s taken the simple approach, with the core of the ontology focused around classifying ingredients, nutrients and food. “We have started with the simplest ontology and focused on the most common use case — mobile recipe search,” he says.

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Turns out, RDF is not at play here. But natural language processing certainly factors in, albeit from the perspective of information extraction and being almost entirely machine-learning based rather than deep-parsing oriented. The service’s technology is influenced by the expert machine-reading NLP work being done at the University of Washington, where Wavii advisor Oren Etzioni is a professor of computer science.

But Wavii CEO and founder Adrian Aoun can credit growing up in a household where his father was a linguist — a student of Noam Chomsky – for originally sparking his interest in how language works. Whenever his dad would have a debate about a language construct with his fellow MIT buddies, he says, “they’d turn to me and say which one sounds better….The irony is that they’re arguing over the rules, but they acknowledge the right answer is whatever humans do.”

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Executive Summary

Chemistry is an important and high-value vertical in the modern world and the "semantification" of chemistry will be crucial for further rapid innovation not only in the discipline itself, but also in related areas such as drug discovery, medicine and materials design. This article provides a short overview over the current technological state of the art in semantic chemistry and also discusses some obstancles, which have, so far, impeded the widespread uptake of chemistry in the domain.

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