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Phone: +1 (727) 498-0222

E-Mail: info@appliedrelevance.com

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Brochures

Please take one of our lovely brochures.  They are suitable for framing.  Not only decorative, they are also enlightening.

AR.Taxonomy Data Sheet

DataFocus for Oracle SES

AR.Taxonomy for Sharepoint 2007

Wand Foundation TaxonomiesDataFocus for MOSS 2007

AR.Taxonomy

AR.Taxonomy is a Windows application that allows you to author rule-based categories. AR.Taxonomy provides an intuitive interface which allows you to create taxonomies for Microsoft Office Sharepoint Server 2007, Oracle Secure Enterprise Search, Apache Solr and many other enterprise search and document management applications.

Taxonomy Authoring

  • Interactively create and edit taxonomy nodes.
  • Create new taxonomy
  • Drag-and-drop taxonomy hierarchy authoring
  • Cut/Copy/Paste nodes
  • Convenient breadcrumb navigation
  • Import Verity K2 .tax files
  • Import Verity .otl files
  • Import Autonomy Category XML files
  • Import from SchemaLogic controlled vocabularies.

Business Rules

  • Build business rules with powerful Lucene query language.
  • Test business rules in real-time against built-in full-text index.

Preview

  • View document in built-in browser.
  • View all indexed metadata for document.
  • View matching categories for the document.
  • View a plain-text (filtered) version of the document.

 

Download the AR.Taxonomy Data Sheet.

AR.Taxonomy is a taxonomy builder application with a rich user interface for knowledge architects, librarians and subject matter experts.

AR.Taxonomy uses a simple, powerful query language similar to that used by Google, MSN Live and Yahoo!.

  • Test category node queries in real-time against the full-text index.
  • Drag and drop taxonomy nodes, execute full-text and meta-data queries
  • Preview matching documents and see how AR.TaxonomyServer will augment the document meta-data in the index.

Our Philosophy

Over the years, many solutions for automatically generating taxonomies have appeared on the market.   Our customers have tried to make them work.   Invariably, they end up throwing away the automatically generated taxonomies and build them by hand using rule-based categories.

While search engine vendors continue to sell the magic beans of auto categorization, we see the same limitations over and over again.  Not matter how sophisticated the algorithm, auto categorization still doen't pass the smell test - let alone the Turing test.

The "traditional" process for autocategorization relies on linguistic and statistical analysis of some set of documents.   While these algorithms are impressive, and are sometimes able to tease out some interesting relationships, they are very unreliable compared to a humans.  Your brain can always beat out a computer for understanding meaning.   A computer understands meaning as well as my pet snail understands trigonometry.