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 (continued at: )

I'm looking for something along the lines of TopicMaps or
XFML wrt topic hierarchies; but need also to be able to
optionally associate a set of weighted regular expressions 
with each topic. This lets the topics do other "concept-based"

Notes: Concept-based systems, Thesauri, TopicMaps

Word Wranglers
Automatic classification tools transform enterprise documents from "bags of words" into knowledge resources

Support Vector Machine
Auto-Categorization: Coming to a Library or Intranet Near You! 
(Nov 2002)


''[BOT] Concept Dictionary. This is a set of topics and 
subtopics about drugs. Manually, a set of weigthed generating 
terms were added. A spider searches the web for stories related 
to drugs and automatically assigns topics to these stories. The 
end results gets exported in this XFML feed, which is the first 
known case of someone using the occurrence strength concept 
which lets you indicate how much trust you have in the 
occurrence. I say cool.''
Yay! Someone gets it :-)

The next scenario I can imagine is as a way 
of producing a consolidated "on-topic" feed from 
a number of other feeds.  Combined with technology 
to scrape RSS from sites and databases and with a 
little automagic to add topics where they don't 
exist this could be very powerful.

''The idea is to produce a facility within liveTopics for 
suggesting topics based upon the text entered in a post.  
At the moment there is a simple facility based upon a 
word search for existing topics, I'm keen to improve upon 
that in the future.''


Untangling Text Data Mining (TDM), LINDI Project,
Interesting RSS, XFML, FOAF discussions

Syndication News from Bill Kearney

Mind your phraseology!
Using controlled vocabularies to improve findability

XFML Core is an open XML format for publishing and sharing 
hierarchical faceted metadata and indexing efforts. XFML Core is 
lightweight and easy to implement, yet uniquely powerful.

XML Topic Maps

Ontology for describing topic hierarchies

Concept-Based Systems

ArchiText .... Excite (history)

Sun Labs: Conceptual Indexing/Retrieval
Improving your ability to find information online 
Conceptual Indexing
for Precision Content Retrieval

DCARS (Document Content Analysis and Retrieval System)

As military organizations continue to collect and store 
increasing amounts of electronic textual documents, users need 
automated tools to facilitate precise timely retrievals. The 
Information Directorate, in collaboration with the National Air 
Intelligence Center (NAIC), developed the Document Content 
Analysis and Retrieval System (DCARS) to permit users to 
retrieve text documents with increased speed and precision from 
the Central Information Reference and Control Repository. DCARS 
uses a state-of-the-art search engine that includes several 
dictionaries and a thesaurus. The directorate's Global 
Information Base Branch and NAIC developed tools to convert 
military thesaurus and acronym lists for easy integration into 
DCARS by adding a higher recall capability. Directorate 
engineers extended DCARS technology to the World Wide Web as 
WebDCARS. DCARS/WebDCARS provides full text document search and 
retrieval along withnatural language and Boolean searches.

Concept Based Information Retrieval

Software brings new power to content tagging and data mining
''Concept-based indexing translates phrases and words to their
 underlying clinical concepts, for example, "heart attack",
 "myocardial infarction" and "MI" would all index to the
 same concept. Concept-based retrieval translates the user's
 search words and phrases to the same set of concepts. The
 result is consistent, comprehensive retrieval of the right
 healthcare information.

Enhancing Internet Search Engines to Achieve Concept-based 
Retrieval Fenghua Lu1, Thomas Johnsten2, Vijay Raghavan1 and 
Dennis Traylor3

Theme Extraction - How it Works 
  Active Navigation theme extraction technology is at the core 
of Portal Maximizer's power. Our theme extraction is based on 
proven linguistic and statistical mining techniques to ensure 
that themes truly reflect the meaning of content and guarantee 
that context is maintained throughout the entire information 
discovery process.
(concept based)

AFRL Enhances Precision Document Retrieval and Electronic Mail