Autonomy Launches New Eduction™ Module for 'Next Generation' of Automatic Metadata Inference Processing
San Francisco, Calif. - January 20,2003- Autonomy Corporation plc (Nasdaq: AUTN; LSE: AU., Nasdaq Europe: AUTN), a global leader in infrastructure software for the enterprise, today announced the release of the Autonomy Eduction™ module. The Autonomy Eduction module automatically analyzes unstructured text and extracts the pertinent information in order to form complex metadata. Metadata is the information that describes the document type and content, and is used to improve information retrieval, navigation, storage and transfer within the enterprise. Autonomy's automatic technology which underpins the Intelligent Data Operating Layer (IDOL) into which the new Eduction module fits, not only removes the manually intensive and costly process of creating complex metadata, but produces it in real time.
"Information is the bedrock upon which enterprise business rests," said Sue Feldman, Research Vice President of the Content Management and Retrieval Software program at IDC. "Adding metadata automatically to documents improves search performance and also creates navigation tools like directories so that users can browse in order to locate information. As the amount of unstructured information multiplies, manual metatagging based on key words is not a scaleable solution. Next generation enterprise applications must incorporate automated content technologies as well as database technologies that understand content in order to make the wealth of information easily accessible."
In the past, rigid database management tools that limited extraction to manually created and narrow fields, restricted organizations seeking to use complex meta-data. Autonomy provides the ability to intelligently extract relevant information from unstructured data based on a conceptual understanding of the item rather than relying solely on traditional noun phrase methods.
With Autonomy's technology, a business can channel all manner of information such as phone numbers, URLs, interest rates, serial numbers contained in unstructured file formats into any location or database based on the type of information it is. For example, Autonomy Eduction recognizes that the sequence of characters "johnshaw@email.com" is an email address and associates it with the name "John Shaw" enabling business to group and order data more effectively. Ordinarily, this operation would be dependant on a manual process.
Autonomy's technology extracts information contained in repositories, including meta-data stored in database records, file records and on Internet pages. Once this information is captured and processed through Autonomy's Intelligent Data Operating Layer all applications built upon this layer can take advantage of the meta-data and the business rules they embody. Autonomy's Eduction module can be customized to organize new information via user defined rules in the plain tagging process, through concept-value tagging which uses predefined models to train by example or through a combination of both methods.
"Companies are faced with so much information both new and old that it becomes difficult to manage-an automatic solution to bring order to unstructured information is a necessity in today's competitive environment," said Mike Lynch, CEO and cofounder of Autonomy. "Based on Autonomy's core IDOL technology, the Eduction module offers an efficient solutions for leveraging any form of data to drive the business decision process."
Eduction Features
Simple tag training by example
Plain and concept value tagging
Negative training
Default user definable phrase tags
Case sensitive user defined phrase tags
Configurable length of tags
Configurable address formats (selection of street, zip code, post code, house number, etc.)
Sophisticated text analysis non reliant on strict format
Easy configuration through the Autonomy Category Definition Editor
Autonomy's unique Intelligent Data Operating Layer (IDOL) integrates unstructured, semi-structured and structured information from multiple repositories through an understanding of their content. Autonomy grants enterprises the flexibility to use advanced information retrieval or legacy-based approaches. At the heart of Autonomy's software is its ability to process text, voice and video and identify and rank the main concepts within them. It then automatically categorizes, links, summarizes, personalizes and delivers that information. Autonomy's technology also drives collaboration across the enterprise and enables organizations to effectively leverage expertise. Autonomy's infrastructure technology is used to automate operations within enterprise information portals, customer relationship management, knowledge management, business intelligence and e-business applications, among others.
About Autonomy
Autonomy Corporation plc (Nasdaq: AUTN; Nasdaq Europe: AUTN; LSE: AU.) is a global leader in infrastructure software for the enterprise. Autonomy's technology powers applications dependent upon unstructured information including e-commerce, customer relationship management, knowledge management, enterprise information portals, enterprise resource planning and online publishing. Autonomy's customer base includes more than 575 global companies, including Hutchison 3G, Channel 4, Deutsche Bank, AT&T, AstraZeneca, BAE Systems, Ford, Ericsson, General Motors, Lucent, Royal Sun Alliance, Sun Microsystems and public sector agencies including the UK Government's Department of Trade and Industry, NASA, the US Department of Defense and the US Department of Energy. Strategic reseller and OEM partners include leading companies such as BEA, Business Objects, Computer Associates, Hewlett Packard, IBM Global Services, Oracle, Vignette and Sybase. The company has offices in North America, Europe, Asia and Australia and is on the Web at www.autonomy.com.
Caution Concerning Forward-Looking Statements
With the exception of historical information, the matters set forth in this news release are forward-looking statements that involve risks and uncertainties. A number of important factors could cause actual results to differ materially from those in the forward-looking statements. These factors include, among others, technology risks, including dependence on core technology; fluctuations in quarterly results; dependence on new product development; rapid technological and market change; reliance on sales by others; management of growth; dependence on key personnel; rapid expansion; growth of the Internet; financial risk management; and future growth subject to risks. These factors and other factors, which could cause actual results to differ materially are also discussed in the company's filings with the United States Securities and Exchange Commission, including Autonomy's Annual Report on Form 20-F and Registration Statements on Form F-1.
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