Finding an expert can be tricky. It’s hard to know whom to trust, and even harder to know if they’ll respond to requests for help. Within large corporations and organizations where specific expertise is a prized commodity, this can be a significant day-to-day problem.

This week, at the Computer-Human Interaction (CHI2009) conference, in Boston, computer scientists demonstrated ways to find experts more accurately. Using data-mining techniques, software can help determine what skills a person practices regularly, and how likely she is to respond to requests for help.

Large businesses often keep information about employees’ expertise in a central directory or database. But expertise is difficult to assess with a simple search query, explains Volker Wulf, an associate professor at the University of Siegen, in Germany. It’s an attempt to model knowledge–an abstract concept that’s tricky for a computer to understand. Wulf’s work focuses on digging deeper than a job description or corporate directory, while also respecting a person’s privacy.

Some software, such as IBM’s Altas, can automatically build profiles of employees within an organization, but this tends to be too invasive, Wulf says. Other approaches, such as allowing users to fill out their own profiles, require too much work from them and can be unreliable.

Wulf and his colleagues built a system that searches through parts of a person’s computer to determine her areas of expertise. If an organization deploys the system, its employees can build their own profiles, but they can also designate folders to be searched automatically. The system mines the documents in those folders for keywords that suggest the user’s area of expertise. For example, if an employee has saved lots of files discussing JavaScript and other Web programming topics, the system will conclude that she is an expert in these areas. It will then send this information to a central server, which functions as the clearinghouse for all users’ profiles. The benefit, Wulf says, is that the system can get a true sense of the user’s expertise, including how it changes over time, without poking into areas that people don’t want exposed publicly.

In addition to identifying areas of expertise, N. Sadat Shami, an IBM researcher, says that it’s equally important to figure out which experts are most likely to respond to requests for help. “If the person doesn’t respond, the whole search is futile,” he says.