Jennifer Zaino
SemanticWeb.com Contributor

Dreaming of a castle in Spain? A hideaway on Florida’s Gulf Coast? A cabin in the mountains anywhere — as long as it’s far away from civilization?

Apparently, you’re not alone. Recession or not, there’s enough disposable income out there to power the second-home lifestyle, and that’s a lifestyle now being capitalized on by semantic web start-up SecondSpace. SecondSpace operates ResortScape.com and Landwatch.com, as lifestyle matchmaking services for those who want the most accurate information on properties that meet their very specific requirements. Instead of searching for, say, a two-bathroom, four-bedroom home in a specific neighborhood, as you normally would for a primary residence, the semantic search behind SecondSpace lets users search for the second home of their dream by entities and attributes.

An entity is anything SecondSpace can model with attributes around it — a home, for example, can be defined by attributes that include its square footage but also that it is close to a golf course. So, for example, you can look for a 3-plus bedroom condo near Miami Beach with a pool and spa, or over 40 acres in Montana with power available, or 20+ acres in northwestern Montana with a view of the lake, or a home in Westchester, New York, near a golf course.

The technology behind SecondSpace enables it to infer a lot of information about the surroundings and lifestyles associated with properties that wouldn’t normally be catalogued by a realtor or individual listing a property. That information can be critical to purchasers whose primary residence may be very far from the property they want to buy, and who may not know enough about the area to get a comprehensive view of all their options. For instance, they may know they want a location in Florida close to the beach, but if they hail from overseas their experience of Florida may have been limited to a single visit to Miami, and thus it would be difficult for them to pinpoint specifically what area they are looking to buy a home in, says Gary Cowan, director of product management.

“We can bring the relationships between entities to the user in a logical fashion,” says co-founder and CTO Alok Sinha. For example, you can search for a home in Florida — specifically a condo near the beach at a certain price, and get a comprehensive list of properties in South Beach, Amelia Island, Pompano Beach, St. Augustine, and more. Those searches can be further narrowed — for example, you can further specify that you want that property to have access to a tennis court and golfing. “We use semantic search as the best way to surface our properties, articles, and content modules,” says Sinha.

Feeding these relationships is a whole bunch of data, gigabytes worth. Geo-meronymy is an example of its intelligent indexing, using patterns and verified domain data. SecondSpace can look at all the geometric data in the world, so that the latitude/longitude coordinates of each property are matched with other sources of geographic and spatial data. SecondSpace can take just the coordinates of a property and its square footage and supplement it with area information, climate information, and anything else that represents that property and why someone would be interested in it. Currently it is rich in data in the U.S. in this respect, and by August expects to be equally rich in Canada, India and Mexico.

So, for example, the geometric data for every body of water in the U.S. is mapped against other data from, say, a geographical survey or natural resources database, which can be used to figure out what kind of fish inhabit a particular lake, and this information can be mapped against homes close to these kinds of lakes with those kinds of fish.

“So if a user comes in and says, I want to buy a home where I can do different kinds of trout fishing, we know that trout-fishing happens in fresh water, and here are the fresh water sources,” says SecondSpace architect Delane Hewett. “They probably are interested in the best sources of these types of fish. so we can rank the results and create this trout fishing lifestyle.”

Its underlying technology also understands the proximity between locations, so that users searching for property in, say, Cabo San Lucas, may surface a great place in one of the many little towns just a couple of miles outside those environs that may be exactly what they want — but which they might not ever have learned about otherwise.

SecondSpace has grown from 600 to nearly one million properties now. “We’re designed to extend to as many as 10,000 attributes about a property that we can store and represent massive metadata on, get it provided explicitly to us, derive it, and verify it against data sources,” says Hewett.

As the site expands to encompass more properties worldwide, part of the work will be continually managing synonyms around site descriptions. For example, people hailing from Texas use “creekside” to indicate a waterfront property, while different individuals might equally search for a flat in Mumbai or a condo in Bombay — and mean the same thing. “As you expand worldwide you have to digest more and more a wealth of synonyms about what people mean semantically,” says Sinha.

SecondSpace can work with data sets in multiple formats, including RDF and RSS, though that’s not very readily available yet. Hewett says at some point, as there are more data sharing and application opportunities, its small case semantic web effort may become more of an upper case semantic web play.

“A lot of people are focusing on semantic arguments,” he says. “Everyone has opinions, but without a solid success model that people are raving about, no one knows what the killer semantic web application is. It’s so hard to sit and talk about different technologies and standards if you don’t understand what you are trying to solve. We approached this initially from the lower case semantic web perspective. If we can put people in touch with properties they want, with a human language-type search capability–that means the underlying model is rich enough to represent the semantic web and we can expand in multiple different directions.”

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