| Abstract
|
Information retrieval and integration syst … Information retrieval and integration systems typically must handle incomplete and inconsistent data. Current approaches attempt to reconcile discrepant information by leveraging data quality, user preferences, or source provenance information. Such approaches may overlook the fact that information is interpreted relative to its context. Therefore, discrepancies may be explained and thereby resolved if contexts are taking into account. In this paper, we describe an information integrator that is capable of explaining its results. We focus on using knowledge of an assumption context learned through decision tree-based classification to inform the explanations. We further discuss some benefits and difficulties of applying assumption context in information retrieval. Finally, we indicate how to use Inference Web to explain discrepancies resulting from information retrieval and integration applications. on retrieval and integration applications.
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| Address
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Washington, D.C. +
|
| Author
|
Honglei Zeng +,
Deborah L. McGuinness +,
Paulo Pinheiro da Silva +,
Richard Fikes +
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| Bibtype
|
inproceedings +
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| Booktitle
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International Symposium on Explanation-aware Computing, AAAI Symposium +
|
| Key
|
KSL-05-08 +
|
| Modification dateThis property is a special property in this wiki.
|
9 July 2009 14:39:48 +
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| Month
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November +
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| Note
|
Extended Abstract. +
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| Paper
|
KSL-05-08.pdf +
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| Paper url
|
http://www.aaai.org/Papers/Symposia/Fall/2005/FS-05-04/FS05-04-011.pdf +
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| Tag
|
Computer science +
|
| Title
|
Explaining Results from Information Retrieval and Integration +
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| Tr id
|
KSL-05-08 +
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| Year
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2005 +
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| Categories |
Workshop Paper,
Proceeding Paper,
Publication,
KSL Technical Report
|
