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Improving your ability to find information online
Conceptual Indexing
for Precision Content Retrieval
Can't find what you want?
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How often have you failed to find what you wanted in an online search because
the words you used failed to match words in the material
that you needed? Concept-based retrieval systems attempt to reach
beyond the standard keyword approach of simply counting the words
from your request that occur in a document. The Conceptual Indexing
Project is developing techniques that use knowledge of
concepts and their interrelationships to find
correspondences between the concepts in your request and those
that occur in text passages. Our goal is to
improve the convenience and effectiveness of online
information access.
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The Paraphrase Problem
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The central focus of this project is the "paraphrase problem," in which
the words used in a query are different from, but conceptually related to,
those in material that you need.
For example, in a collection of articles by James Fallows, then Washington
editor of the Atlantic Monthly, the query, "change in the deficit,"
results in several relevant passages including "Last year's reductions in tax
rates are part of the reason for the deficits, as are the administration's
plans for a sustained military buildup." Based on this passage a user can
then decide whether to read the rest of the article. While the query and
the passage convey similar ideas, the wording in each is different, a typical
case of the paraphrase problem.
In addressing the paraphrase problem, three challenges must be met:
- What information is required to connect the terms in a query to
those in a relevant passage?
- How can this information be organized and used efficiently?
- To what extent can descriptions of the content of a document be
automatically extracted from the document itself?
Our approach to the paraphase problem is to identify and extract concepts (meaningful words and phrases), and relate similar concepts to one another. This information is organized in a structured conceptual taxonomy. Presented with a
query, the technology searches through the taxonomy for similar, but not necessarily identical ideas. With special retrieval algorithms, the taxonomy can be scanned efficiently.
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Elements of the Technology
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The technology, which is called "Precison Content Retrieval," is composed of two parts:
- Conceptual Indexing
Builds a structured conceptual taxonomy of words and
phrases extracted from the indexed material
- Specific Passage Retrieval
Finds specific passages and ranks them according to relevance
to the query
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For more information about the Conceptual Indexing Project, contact indexing-info@east.sun.com. Sun Microsystems Laboratories (Burlington, MA)
Knowledge Technology Group, Sun Microsystems Laboratories
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