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(1 - 6 of 6)
- Title
- The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams (semester?), IPRO 338: IPRO Knowledge Management System IPRO 338 Abstract F04
- Creator
- Hendrickson, Dusty, Haque, Nadim S., Hochstetler, Ryan, Jenkins, Adam, Khan, Atif, Swanson, Eric, Riego De Dios, Mark, Thornton, Vance
- Date
- 2004-12, 2004-12
- Description
-
During the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management...
Show moreDuring the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management system (KMS) called “iKNOW” for the Interprofessional Projects (IPRO) program at Illinois Institute of Technology
Deliverables for IPRO 338: The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams for the Fall 2004 semester
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- Title
- The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams (semester?), IPRO 338: IPRO Knowledge Management System IPRO 338 Final Report F04
- Creator
- Hendrickson, Dusty, Haque, Nadim S., Hochstetler, Ryan, Jenkins, Adam, Khan, Atif, Swanson, Eric, Riego De Dios, Mark, Thornton, Vance
- Date
- 2004-12, 2004-12
- Description
-
During the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management...
Show moreDuring the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management system (KMS) called “iKNOW” for the Interprofessional Projects (IPRO) program at Illinois Institute of Technology
Deliverables for IPRO 338: The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams for the Fall 2004 semester
Show less
- Title
- The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams (semester?), IPRO 338: IPRO Knowledge Management System IPRO 338 IPRO Day Presentation F04
- Creator
- Hendrickson, Dusty, Haque, Nadim S., Hochstetler, Ryan, Jenkins, Adam, Khan, Atif, Swanson, Eric, Riego De Dios, Mark, Thornton, Vance
- Date
- 2004-12, 2004-12
- Description
-
During the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management...
Show moreDuring the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management system (KMS) called “iKNOW” for the Interprofessional Projects (IPRO) program at Illinois Institute of Technology
Deliverables for IPRO 338: The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams for the Fall 2004 semester
Show less
- Title
- The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams (semester?), IPRO 338: IPRO Knowledge Management System IPRO 338 Project Plan F04
- Creator
- Hendrickson, Dusty, Haque, Nadim S., Hochstetler, Ryan, Jenkins, Adam, Khan, Atif, Swanson, Eric, Riego De Dios, Mark, Thornton, Vance
- Date
- 2004-12, 2004-12
- Description
-
During the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management...
Show moreDuring the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management system (KMS) called “iKNOW” for the Interprofessional Projects (IPRO) program at Illinois Institute of Technology
Deliverables for IPRO 338: The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams for the Fall 2004 semester
Show less
- Title
- The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams (semester?), IPRO 338
- Creator
- Hendrickson, Dusty, Haque, Nadim S., Hochstetler, Ryan, Jenkins, Adam, Khan, Atif, Swanson, Eric, Riego De Dios, Mark, Thornton, Vance
- Date
- 2004-12, 2004-12
- Description
-
During the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management...
Show moreDuring the fall of 2004, IPRO 338 will continue the work of three previous IPRO teams in developing and implementing a knowledge management system (KMS) called “iKNOW” for the Interprofessional Projects (IPRO) program at Illinois Institute of Technology
Deliverables for IPRO 338: The IPRO Knowledge Management System Improving the Effectiveness of IPRO Teams for the Fall 2004 semester
Show less
- Title
- Efficient management of uncertain data
- Creator
- Feng, Su
- Date
- 2023
- Description
-
Uncertainty arises naturally in many application domains. It can be caused by an uncertain data source (sensor errors, noise, etc.). Data...
Show moreUncertainty arises naturally in many application domains. It can be caused by an uncertain data source (sensor errors, noise, etc.). Data preprocessing techniques (data curation, data integration, etc.) can also results in uncertainty to the data. Analyzing uncertain data without accounting for its uncertainty can create hard to trace errors, with severe real world implications. Certain answers are a principled method for coping with the uncertainty that arises in many practical data management tasks. Unfortunately, this method is expensive and may exclude useful (if uncertain) answers. Other techniques from incomplete database record and propagate more detailed uncertainty information. However, most of these approaches are either too expensive to be practical, or only focus on a narrow class of queries and only work for a specific representation. In this thesis, we investigate models and query semantics for uncertain data management and present a framework that is general and practically efficient, backed up by fundamental theoretical foundations and with formally proven correctness guarantees. We first propose Uncertainty Annotated Databases (UA-DB), which combine an under- and over-approximation of certain answers to combine the reliability of certain answers with the performance of a classical database system. We then introduce attribute-annotated uncertain databases (AU-DB), which extend the UA-DB model with attribute-level annotations that record bounds on the values of an attribute across all possible worlds. AU-DB extends UA-DBs to encode a compact over-approximation of possible answers which is necessary to support non-monotone queries including aggregation and set difference. With a further extension to AU-DB that supports ranking and windowed aggregation queries using native implementation on modern DBMS, our approaches scale to complex queries and large datasets, and produces accurate results. Furthermore, they significantly outperforms alternative methods for uncertain data management.
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