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Data Mining for Airfares

来源: 作者:互联网作品 发布时间:2007-03-31

On a flight to his brother's wedding in 2001, Oren Etzioni discovered that the people sitting next to him had bought their tickets later than he did, yet had paid less. For some, this could have been an infuriating revelation, but Etzioni didn't get mad; as a professor of computer science and engineering at the University of Washington, in Seattle, he got inspired. "I thought, 'Why don't I collect historical data [on airfares] and use that to anticipate ticket prices?'"

商业智能

In 2003, Etzioni and colleagues published a paper showing that they could predict the fluctuation in airline-ticket prices surprisingly well. By sifting through the history of more than 12,000 airfares for nonstop flights from Seattle to Washington, D.C., and from Los Angeles to Boston, the researchers could predict with 62 percent accuracy whether or not those ticket prices would rise or fall in the future. That same year, using the principles behind that research, Etzioni founded Farecast, a website--available to the public in 2006--that advises a visitor whether to buy a given ticket immediately or wait to get a better deal. Earlier this month, the company added a new feature to the site that unearths deals for weekend escapes, family getaways, last-minute excursions, and other types of trips. 搜索引擎

Anyone who has made travel arrangements online knows how quickly airfares can change. Etzioni's early research revealed that a ticket price can change as many as seven times a day, depending on the prices of similar flights from competing companies and on such factors as seat availability on the flight in question. The capricious and opaque nature of airfare has inspired other entrepreneurs to start companies that try to help consumers make the most economical decisions. FareCompare tracks airline sales and promotions that fall in line with a user's preset constraints. Another site, called Kayak, displays the best ticket prices found by Kayak users over a two-day period. 商业智能

Farecast differs from these companies by using sophisticated algorithms to mine enormous data sets of more than 175 billion airfares from around the country. This data is collected by Boston-based ITA Software, a company that works with airlines and travel sites such as Hotwire and Orbitz to help with pricing and reservations. Farecast's data-mining algorithms look for trends in the prices and help determine the impact on prices of variables such as seasonal changes, conventions, and college graduations. But humans also play an important role in analysis, explains Etzioni. Farecast's engineers look at the data using specialized visualization software--collections of plots and graphs that can show multiple variables and changes over time. "Our variables can be quite complex, and we use the human eye and highly evolved visual cortex to discern patterns," Etzioni says. Sometimes, a trend or anomalous variable will be subtle and missed by a computer, he says, but when displayed graphically, it can be caught by a person.

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