Meaning Based Computing: The Future of Enterprise Search

A trend toward client/server architectures and open systems defined the 1990s. More recently, service oriented architecture (SOA) and grid computing have been the rage. These initiatives transformed computing by improving the ways in which computers work together, while reducing the potential for system failures.

Today, with the amount of data in the word doubling every year and an explosion in people friendly information such as email, IM, voice and video, a new movement in computing has emerged - one that dramatically changes the way in which people work with computers. Aptly named Meaning Based Computing, this movement is more powerful than any architectural change in computing as it is being driven by a significant change in the data people and organizations need to process.

Over the past few years the nature of the information organizations are dealing with has changed dramatically – from structured data that can be organized neatly into rows and columns in a database - to unstructured data including audio, video, web pages, email, blogs and instant messaging. This is data that cannot be so easily organized. Today, more than 80% of all information in an enterprise is unstructured creating both a challenge and an opportunity for the enterprise. The challenge lies in how to access this information effectively; the opportunity in using that information to gain true business insight and mitigate the risks associated with not managing that information effectively.

In fact, being able to manage and process this data has become, for many organizations, a strategic imperative. One of the key drivers for this is the evolving regulatory climate, with new directives such as the recent Federal Rules of Civil Procedure demanding that organizations have set policies and procedures in place to ensure that electronically stored information in whatever form is discoverable. The ability to forensically track and trace each piece of data that enters, leaves, is created or destroyed within the organization is now a critical requirement.

Against this backdrop, more and more organizations have realized that merely being able to find information through traditional keyword search methods is insufficient. To gain true business insight they need to be able to understand the meaning of the data in a timely and efficient manner. This is where Meaning Based Computing comes in.

Meaning Based Computing, signals the ability of computers to comprehend the concepts and context of unstructured data, enabling people to extract significant value from it. Meaning Based Computing extends far beyond Keyword Search, which simply allows users to find and retrieve data; instead Meaning Based Computing systems understand the relationships that exist between disparate pieces of information and perform sophisticated analysis operations, automatically and in real-time. Leading technology analysts say delivering the richness of meaning to users is pivotal to overcoming the deficiencies of keyword search - especially with information in the typical enterprise doubling in volume every six to 12 months.

Significantly, some of the key functionality of Meaning Based Computing such as automatic hyperlinking and clustering are simply not available in keyword search engines. For example, automatic hyperlinking which connects users to a range of pertinent documents, services or products that are contextually linked to the original text requires that the meaning of the original document is fully understood. Similarly, for computers to automatically collect, analyze and organize information, computers have to be able to extract meaning. Only Meaning Based Computing Systems can do this and Autonomy is the leader in this rapidly growing area.

In order to deliver on the vision of Meaning Based Computing, technologies must be tightly integrated into the infrastructure platform; not be a collection of other vendors’ products marketed as one platform. Autonomy’s Intelligent Data Operating Layer (IDOL) provides the foundation for Meaning Based Computing. This comprehensive platform allows for the conceptual and contextual understanding of all forms of information, with more than 500 functions applying Meaning Based Computing processes to unstructured, structured and semi-structured data.

Meaning Based Computing Goes Mainstream

Meaning Based Computing was borne out of extensive research on advanced pattern-matching and concept extraction at prestigious institutions such as MIT, Wharton and Cambridge University. Leading academics at these centers of excellence determined that there are patterns which naturally occur in text, based on the usage and frequency of words or terms, and that these correspond to specific ideas or concepts. Based on the preponderance of one pattern over another, computers can automatically understand that there is a probability that a document is about a specific subject and extract a document’s digital essence or meaning. This revolution in computing meant that computers could, for the first time, form an understanding of a page of text, web pages, emails, conversations, and video broadcasts, entirely automatically.

“Conventional technologies use keywords or frequency of associations of keywords to identify specific information. However, this approach has limitations due to the multiple definitions of some words. A much better approach is to use a concept-based methodology that understands the real meaning of words in their
correct context.”
Susan Clarke, Butler Group

Early Adopters of Meaning Based Computing Platforms

Early adopters of this cutting-edge technology included government and intelligence agencies. Over a decade ago, these organizations began to invest portions of their IT budgets into Meaning Based Computing, a technology few had even heard about. Today, the U.S. Department of Homeland Security (DHS) delivers intelligent homeland protection across government agencies including Defense, Commerce, Energy, Transportation, Justice, U.S. Customs Food and Drug and Health and Human Services. DHS is deploying Meaning Based Computing to link up to 200,000 employees of the 21 agencies in order to enable homeland security related agencies to monitor suspected terrorist groups and create a consolidated terrorist watch list.

In addition to intelligence agencies in the U.S and Europe, numerous global software companies and systems integrators have since developed and implemented applications that rely on Meaning Based Computing. BEA, BearingPoint, Cognos, EDS, IBM Global Services, Vignette, Stellent and Symantec are a few of the software companies and service providers that are already delivering the value of Meaning Based Computing to their customers. Similarly, a number of enterprises have followed suit and placed their most vital asset, knowledge, held in both electronic form and in people, into the hands of Meaning Based Computing systems. The number of these organizations increases everyday and the following is a mere selection: BAE Systems, Boeing, Ford, Daimler Chrysler, Shell, AOL, BBC, Reuters, Hutchison 3G, Ericsson, T-Mobile, Philips, Coca Cola, Kraft Foods, Nestle, Lloyds TSB, GlaxoSmithKline, KPMG, Citigroup, ABN AMRO, Deutsche Bank, Nomura, the U.S. Securities and Exchange, the U.S. Department of Homeland Security, NASA and the U.S. Department of Energy.

The movement to Meaning Based Computing, which includes infrastructure platforms and applications for understanding unstructured information, continues to intensify in 2006 as the IT industry seeks better ways to serve the needs of global corporations and government agencies.

The Components of Meaning Based Computing
The components of Meaning Based Computing include an infrastructure platform for understanding and processing unstructured data and the applications that rely on the value contained in that information.

The Infrastructure Platform

The Meaning Based Computing platform is becoming a required component of Enterprise Information Management (EIM) architecture as IT departments seek to unify structured and unstructured information across their organizations. Gartner defines EIM as “an organizational commitment to structure, secure and improve the accuracy and integrity of information assets; to solve semantic inconsistencies across all boundaries; and support the technical, operational and business objectives within the organization’s enterprise architecture strategy.”

Meaning Based Computing platforms, such as Autonomy’s IDOL, are capable of processing any type of information from virtually any source. They can automatically aggregate as many as 1000 different file formats, including voice and video content, from the most comprehensive range of repositories available including document management systems, email servers, Web servers, relational database management systems, file systems, legacy systems and others. In this way, the Meaning Based Computing platform allows enterprises to extract meaning by relating seemingly unrelated information from disparate sources.

The Applications

Meaning Based Computing platforms are enabling a new breed of strategic applications across a wide range of industries including investment banking, pharmaceutical, energy, media and others. These applications include:

Advanced Enterprise Search

Meaning Based Computing platforms provide organizations with sophisticated concept retrieval methods to not only uncover, but also make sense of, the 80% of enterprise information that is hidden to all other technologies including keyword search engines and relational databases. As a result, employees are presented with relevant information they didn’t even know existed so they can act on it in real-time.

Knowledge Management

Meaning Based Computing platforms enable organizations to automatically form a contextual understanding of people’s interests, behavior and ongoing interaction with any type of information, regardless of format, location or device. This facilitates collaboration by leveraging the most valuable knowledge available - the experience and expertise of an organization’s employees. Using Meaning Based Computing, engineers in different locations and business units at an international aerospace firm discovered they were working to solve the same wing and construction problem. Identifying this duplication of work allowed resources to be redistributed and led to significant cost savings.

Product Quality Management

Meaning Based Computing platforms enable manufacturers to perform a real-time analysis on customer communications to quickly identify product issues and emerging consumer trends. For example, quality engineers at a global medical device manufacturer make faster, more informed decisions on product recalls because their Meaning Based Computing platform prioritizes the questions, concerns and comments fielded from more than 8,000 customers every day.

E-Discovery

Meaning Based Computing platforms enable organizations to effectively respond to subpoenas by courts and other regulatory bodies. Extracting meaningful evidence from terabytes of email, documents, spreadsheets and other unstructured information enhances the ability of investigators to make informed decisions about corporate culture and track the development of illegal activity.

Meaning Based Computing signals the dawn of a new phase of interaction between humans, organizations and computers, one where the computer automatically delivers relevant information without us having to ask or search for it or, in the case of criminal investigations and compliance requirements, without us even knowing what we’re looking for. This automatic processing of data will help organizations drive efficiencies across the business, enhancing productivity and competitiveness and ultimately adding to the bottom line.