Functionality Real-Time Predictive Query | Query Federation | Device-Specific Answers
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Automatic Query Federation (AQF)

If the user enters a highly specific query, such as a purchase order code, it is unlikely that any subsystem other than the company's accounts database will return an accurate result. In cases such as this, Autonomy offers Automatic Query Federation (AQF) technology. This module federates the query to a subsystem it has identified as the correct specialist, based on its conceptual understanding of the query itself. For example, if a user enters a shipment tracking number, IDOL recognizes from the form of the query that the shipping company will be most likely to return the correct result, and federates the query to that system.

Autonomy AQF
Autonomy AQF

Built into the technology is the "intelligent ant" function described below. Spiders go out, learn about data and relay the intelligence to the ants. When spiders come across changes in information inside or outside the enterprise, the system switches to ant mode. A mechanism that resembles the chemical signals used by ants notifies the system that user or data properties have changed. Ant trails are automatically established, returning all relevant information. Consequently, AQF is able to update what is happening to rapidly changing data and train itself to use the optimum search technique. For each query, it can identify whether it is better to look in internal applications for data, or whether to search for fresh information and update the index dynamically. In this way, AQF offers unrivalled, intuitive interaction with information for the user and significant productivity improvements for the enterprise.

When Spiders Talk to Ants
The information that drives the enterprise comes from an ever-increasing number of sources. Experts estimate that by the end of 2008, 20% of results in new information access projects will be refreshed every time a query is entered. The average worker is dealing with information overload on a daily basis - how to process it, where to locate it and how to derive meaning from it. Increasingly, workers familiar with consumer search technologies expect access to all forms of data, including information from the Internet, and not just static files.
At the moment, most search engines use spiders that navigate an information web and create a basic configuration of the linked documents. By rebuilding the image from scratch at defined intervals, the spider creates a simplified picture of the overall structure of the network it is searching. In between those time intervals, however, the information can easily become outdated and the results returned irrelevant. Spiders are unable to return real-time, dynamic information.
Ant technologies, on the other hand, respond to the current landscape and deal with rapid changes. Real ants do not formulate a conceptual image of the landscape as they explore; they simply relay new discoveries back to the colony, which responds in a dynamic fashion. Software ants behave similarly, in that each ant will travel familiar paths to find the most relevant piece of information. However, in the Internet Age, ants are required to make periodic investigations of relevant enterprise applications to ensure they locate the optimum route and deliver results quickly.
The solution lies in a hybrid of both technologies where the two work together to access and deliver relevant information. Spiders go about their normal tasks, such as monitoring and analyzing information, then relay the information to an ant. When something changes, ants learn from the variation and can pass it along in real-time. Variations allow ants to adapt and optimize the way in which information is gathered. Systems react instantly because updates are reported immediately and new paths are dynamically created.
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Functionality Real-Time Predictive Query | Query Federation | Device-Specific Answers
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