Content Analytics with Enterprise Search

UIMA framework

Overview

IBM Content Analytics provides a UIMA compliant analytics engine and rich platform for deploying text analytic solutions.

Content Analytics is a platform to derive rapid insight. It can transform raw information into business insight quickly without building models or deploying complex systems enabling all knowledge workers to derive insight in hours or days … not weeks or months. Flexible and extensible for deeper insights, Content Analytics enables better decision making by deriving valuable insights from your enterprise content regardless of source or format. It allows deep, rich text analysis of your information. Solutions built on Content Analytics can help organizations surface undetected problems, fix content-centric process inefficiencies, improve customer service and corporate accountability, reduce operating costs and risks and discover new revenue opportunities.

Unstructured Information Management Architecture (UIMA) is an open framework for building analytic applications - to find latent meaning, relationships and relevant facts hidden in unstructured text. UIMA defines a common, standard interface that enables text analytics components from multiple vendors to work together. It provides tools for either creating new interoperable text analytics modules or enabling existing text analytics investments to operate within the framework.

Although UIMA originated at IBM, it has now moved on to be an Open Source project at the Apache Software Foundation. UIMA is the only recognized standard for semantic search and content analytics, by OASIS (Organization for the Advancement of Structured Information Standards).

Content Analytics can analyze documents, comment and note fields, problem reports, e-mail, web sites and other text-based information sources. Sample Applications

Product defect detection. Analysis of service and maintenance records provides early insight into product defects and service issues before they become widespread, thus enabling quicker resolution and lower after market service and recall costs.
Insurance fraud analysis. Analysis of claims documentation, policies, and other customer information allows organizations to identify patterns and hidden relationships in claims activities to reduce incidents of fraud and unnecessary payouts.
Advanced intelligence for anti-terrorism and law enforcement. Analysts can uncover hidden patterns and identify potential criminal or terrorist activity by better analysis of various information sources such as field analyst reports, surveillance transcripts, public records and financial transactions.
Customer support and self-service. Analysis of call center logs, support e-mails, and other support documentation provides more accurate problem identification to better identify appropriate resolutions.
e-Commerce and product finders. Customers can find both target and complementary products online, and sales reps can make the right cross-sell offer by identifying relationships and concepts from analysis of product content, customer profiles and sales notes.