Oracle Text

Oracle Text uses standard SQL to index, search, and analyze text and documents stored in the Oracle database, in files, and on the web. Oracle Text can perform linguistic analysis on documents, as well as search text using a variety of strategies including keyword searching, context queries, Boolean operations, pattern matching, mixed thematic queries, HTML/XML section searching, and so on. It can render search results in various formats including unformatted text, HTML with term highlighting, and original document format. Oracle Text supports multiple languages and uses advanced relevance-ranking technology to improve search quality. Oracle Text also offers advanced features like classification, clustering, and support for information visualization metaphors.


Technical Information
  Oracle Text in Oracle Database 11g
White Paper (PDF)
New Features (PDF)
 
  Text Mining
Text Mining with Oracle Text (PDF)
Classification and clustering in Oracle Text (PDF)>
Information Visualization with Oracle Text (PDF)
XML Features
 
  Text Performance
Pre-loading Oracle Text Indexes into Memory
MDATA - Tips and Tricks
Progressive Relaxation - improving relevance and recall
The CTXCAT Index type
 
  Other Information
Oracle Text FAQ
Using CTX_REPORT and XML
English Knowledge Base Category Hierarchy (PDF)
 
  Technical Overviews
Oracle Text Technical Overviews

 

Selected Papers and Presentations
TREC Benchmark and Text Retrieval Quality
TREC-8 Quality Benchmark (PDF)
TREC-10 Statistical classification (adaptive and batch) and question-answering (PDF)
Feature Preparation in Text Categorization (PDF)
Setting up an Index Maintenance Regime for Oracle Text
How Oracle Text processes text DML
Using Alternative Filters for Filtering PDF Files
Performance FAQ
Search Enable a Web site
20th Unicode conference presentation (ZIP)
Oracle Text - OOW San Francisco paper (November 2001) (ZIP)
The Last Word in Document Archives - OOW Copenhagen (July 2002) (ZIP)
Oracle Does Search - OW San Francisco (November 2002) (ZIP)
Improving Intranet Search with Database-Backed Technology - OW San Francisco (September 2003) (ZIP)
Try doing this with Google - OW San Francisco (December 2004) (ZIP)
Architecture for a Comprehensive Intranet Search - OW San Francisco (December 2004) (ZIP)
Text Mining with Oracle - Text Mining Summit (June 2005) (PPT)
Toward an Information Grid - OOW San Francisco (September 2005) (PDF)

 

Customer Presentations and Case Studies
H. Ulrich (Der Spiegel) OOW San Francisco presentation (October 2006) (PDF)
Case Study: Motorola (PDF)
Case Study: IronMountain (PDF)
Case Study: World Bank (PDF)
A. Suwalska (CERN) OW Paris (November 2003) (PPT)
L. Keller (OCLC) OOW San Francisco paper (November 2001) (DOC)
L. Keller (OCLC) OOW San Francisco presentation (November 2001) (ZIP)
H. Ulrich (Der Spiegel) OOW Berlin paper (July 2001) (DOC)
H. Ulrich (Der Spiegel) OOW Berlin presentation (July 2001) (PPT)
 
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