The Deep Query Manager™ (DQM) is a content discovery, harvesting, management and analysis platform used by knowledge workers to collaborate across the enterprise. It can harvest documents from the Internet, internal intranets and/or file systems, allowing it to gather information from inside and outside the entire organization.

On the Internet, DQM can access more than 70,000 unique, searchable databases and has automated techniques for your analysts to add new databases at will. It can use hundreds or thousands of search engines to help you find required information. And it can search sites and gather documents from those sites whether they have a search facility or not.

DQM's differencing engine supports Web site monitoring and tracking. It also has very powerful project management, data mining, reporting and analysis capabilities.

DQM is a server-based product, accessed by end-users and system administrators through a browser interface. All leading browsers are supported. DQM's distributed architecture allows your organization to scale up into hundreds or thousands of users across multiple machines as your needs require. As such, it permits the organization to purchase only those server capabilities it currently needs, and then expand its infrastructure incrementally to accommodate growth.

A screenshot depicting the Query tab of the Harvest screen for the Deep Query Manager is shown below (in this case using a query in Russian):

The Search Challenge

It's not easy to find information on the Internet when the search goal's breadth or depth goes beyond that of interest to the general user. In those cases, multiple limitations can arise:

• The required topic is not covered by the general search engines and requires the discovery and use of more specialized search engines
• The required topic or depth may not be available from conventional surface Web sources and may require access to specific database sources of the Deep Web
• The returned information may be replete with similar terms, but unrelated information  requires proper filtering to separate the targeted information from the clutter
• The returned information may require post-processing such as local searching or results comparison
• If the required information changes with time and requires periodic monitoring, taking samples at scheduled intervals might be required.

Search engines, searchable databases and individual Web sites can be scheduled for repeated monitoring and tracking. The powerful difference reporting features mean you don't need to constantly review the same documents — you only need inspect what has changed.