KSL-05-07 + redirect page
Extracting Assumptions from Missing Data + Has identifier
Extracting Assumptions from Missing Data + Ksl tr id
| Extracting Assumptions from Missing Data |
Bibtype
inproceedings
Has publishing details
July,2005
Has title
Extracting Assumptions from Missing Data
Has where published
Context representation and reasoning 2005, proceedings of the first international workshop
Has year
2005
Title
Extracting Assumptions from Missing Data
Year
2005
Abstract
Information integration is the task of agg … Information integration is the task of aggregating data from multiple heterogeneous data sources. The understandings of context knowledge of data sources are often the keys to challenging problems in information integration such as handling missing and inconsistent data. Context logic provides a unified framework for the modeling of data sources; nevertheless, the acquisition of large amounts of context knowledge is difficult. In this paper, we study the importance of a special type of context knowledge, namely assumption knowledge. Assumption knowledge refers to a set of implicit rules about assumptions on which a data source is based. We develop a decision tree classifier to extract assumption knowledge from missing data and formalize the knowledge in context logic. Finally, we build an information aggregator with assumption knowledge reasoning, which is capable of explaining incomplete data aggregated from heterogeneous sources. ata aggregated from heterogeneous sources.
Address
Paris +
Author
Honglei Zeng and Richard Fikes +
Booktitle
Context representation and reasoning 2005, proceedings of the first international workshop +
Has author
Honglei Zeng and Richard Fikes +
Has identifier
Extracting Assumptions from Missing Data +
Ksl tr id
Extracting Assumptions from Missing Data +
Month
July +
Process note
NO +
Categories InProceedings +, KSL Technical Report +, Publication +
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