Simple keyword or text search is not always effective for quickly finding what you need. IBM® has gone beyond keywords by inventing a fast and accurate semantic search system for personal e-mail.

IBM OmniFind Personal E-mail Search enables semantic searching by extracting and organizing concepts and relationships from personal e-mail. Any business e-mail user who must search in order to accomplish a business purpose will find this tool invaluable. Customization of semantic concepts and the ability to share these concepts with colleagues make this tool especially useful for large enterprise customers.

IBM OmniFind Personal E-mail Search is easy to install and configure and automatically adjusts to desktop load.

The new version for Outlook and Notes incorporates two main changes:

• New, state-of-the-art information extraction technology for superior performance and reduced memory consumption. This new version provides the benefits of faster indexing and improved concept recognition.
• The tagger utility is no longer being bundled with the technology, allowing for a leaner installation and a quicker initial set-up. If you are interested in functionality similar to the tagger utility, check out System Text for Information Extraction (another alphaWorks® technology).

How does it work?

Users simply type keywords to express their queries. The tool intelligently matches these queries against pre-defined concepts (such as persons, phone numbers, addresses, or schedules) and relationships amongst such concepts (such as a person's phone number or address). In ambiguous situations, the intelligent search engine will interact with the user in order to determine the user's true intention.

Users can create new concepts using the tagger utility and thereby customize their semantic search. Both system tags and user-defined tags are searched during run time.

The tagger utility also enables users to easily share taggers, thereby promoting community search efficiency and cooperation while keeping their e-mail private.

The components of IBM OmniFind Personal E-mail Search are as follows:

• an e-mail crawler (Lotus Notes/Outlook)
• a document-processing, concept-tagging pipeline
• an indexing component
• a run-time semantic search component
• a tagger utility.

The new versions for Outlook and Notes have improved support for non-English Windows machines. The Outlook version now also supports IMAP and non-cached Exchange accounts. Please see these instructions for configuring Outlook appropriately.

Sriram Raghavan, of IBM""s Almaden Research Center, develops powerful semantic search technology that exploits structured information extracted from text to enable high-precision keyword information retrieval.

Rajasekar Krishnamurthy, Ph.D. (Almaden), focuses on scalability and quality in the context of large-scale information extraction systems and is building a declarative rule-based information extraction system.

Eser Kandogan, Ph.D. (Almaden), is interested in information interaction, user interfaces, semantic search, human interaction with complex systems, ethnographic studies, information visualization, and end user programming.

Yosi Mass (Haifa, Israel) leads several projects, is responsible for numerous patents and publications, and is the father of the "XML Fragments" query language for semantic search in XML and in Unstructured Information Management Architecture (UIMA).

Nadav Har""El (Haifa) works on information retrieval in geographic data mining, desktop search, advanced faceted search, and social search. He created the popular Hspell, an open-source Hebrew spell-checker used by OpenOffice and Google""s Gmail.

Michael Bluger (Haifa) works on textual search, including desktop search. His background is in natural language processing, artificial intelligence, machine translation, agent-based Web search, text analysis and classification, and information retrieval.

Huaiyu Zhu, Ph.D. (Almaden), focuses on infrastructure for text analytics and applications, and, in particular large-scale analytics for enterprise search applications.

Ganesh Ramakrishnan, Ph.D. (India), focuses on information extraction, especially rule and feature induction using inductive logic programming, speeding up of rule-based information extraction techniques, and environments for developing and organizing rules.

Kyna Sah manages projects of IBM""s Information Management (IM) Architecture Board, Advanced Technologies, for the IBM IM Chief Technology Office; her projects include launching new product initiatives at the Information On Demand Conference.

Shivakumar Vaithyanathan, Ph.D. (Almaden), manages the Unstructured Information Analysis group at Almaden and is the technical project leader for IBM OmniFind Personal E-mail Search. He is an associate editor for the Journal of Statistical Analysis and Data Mining.