Techreport1731: Unterschied zwischen den Versionen
Aus International Center for Computational Logic
Markus Krötzsch (Diskussion | Beiträge) K (Textersetzung - „|Forschungsgruppe=Wissensmanagement“ durch „|Forschungsgruppe=Information Systems“) |
Sebastian Rudolph (Diskussion | Beiträge) Keine Bearbeitungszusammenfassung |
||
| Zeile 14: | Zeile 14: | ||
|BibTex-ID=RTH08-approximate | |BibTex-ID=RTH08-approximate | ||
|Title=What Is Approximate Reasoning? | |Title=What Is Approximate Reasoning? | ||
|To appear=0 | |||
|Year=2008 | |Year=2008 | ||
|Month=März | |Month=März | ||
|Institution=Institute AIFB, University of Karlsruhe | |Institution=Institute AIFB, University of Karlsruhe | ||
|Reviewed=Prof. Studer | |||
|Archivierungsnummer=1731 | |Archivierungsnummer=1731 | ||
}} | }} | ||
{{Publikation Details | {{Publikation Details | ||
|Abstract=Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness or completeness for a significant speed-up of reasoning. This is to be done in such a way that the number of introduced mistakes is at least outweighed by the obtained speed-up. When pursuing such approximate reasoning approaches, however, it is important to be critical not only about appropriate application domains, but also about the quality of the resulting approximate reasoning procedures. With different approximate reasoning algorithms discussed and developed in the literature, it needs to be clarified how these approaches can be compared, i.e. what it means that one approximate reasoning approach is better than some other. In this paper, we will formally define such a foundation for approximate reasoning research. We will clarify -- by means of notions from statistics -- how different approximate algorithms can be compared, and ground the most fundamental notions in the field formally. We will also exemplify what a corresponding statistical comparison of algorithms would look like. | |Abstract=Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness or completeness for a significant speed-up of reasoning. This is to be done in such a way that the number of introduced mistakes is at least outweighed by the obtained speed-up. When pursuing such approximate reasoning approaches, however, it is important to be critical not only about appropriate application domains, but also about the quality of the resulting approximate reasoning procedures. With different approximate reasoning algorithms discussed and developed in the literature, it needs to be clarified how these approaches can be compared, i.e. what it means that one approximate reasoning approach is better than some other. In this paper, we will formally define such a foundation for approximate reasoning research. We will clarify -- by means of notions from statistics -- how different approximate algorithms can be compared, and ground the most fundamental notions in the field formally. We will also exemplify what a corresponding statistical comparison of algorithms would look like. | ||
|Download=2008_1731_Rudolph_What_Is_Approxi_1.pdf, 2008_1731_Rudolph_What_Is_Approxi_2.pdf | |||
|Forschungsgruppe=Computational Logic | |||
|VG Wort-Seiten= | |VG Wort-Seiten= | ||
}} | }} | ||
{{Forschungsgebiet Auswahl}} | |||
{{Forschungsgebiet Auswahl}} | |||
{{Forschungsgebiet Auswahl}} | |||
{{Forschungsgebiet Auswahl}} | |||
Version vom 14. Oktober 2014, 20:45 Uhr
What Is Approximate Reasoning?
Sebastian RudolphSebastian Rudolph, Tuvshintur TserendorjTuvshintur Tserendorj, Pascal HitzlerPascal Hitzler
Sebastian Rudolph, Tuvshintur Tserendorj, Pascal Hitzler
What Is Approximate Reasoning?
Technical Report, Institute AIFB, University of Karlsruhe, volume 1731, March 2008
What Is Approximate Reasoning?
Technical Report, Institute AIFB, University of Karlsruhe, volume 1731, March 2008
- KurzfassungAbstract
Approximate reasoning for the Semantic Web is based on the idea of sacrificing soundness or completeness for a significant speed-up of reasoning. This is to be done in such a way that the number of introduced mistakes is at least outweighed by the obtained speed-up. When pursuing such approximate reasoning approaches, however, it is important to be critical not only about appropriate application domains, but also about the quality of the resulting approximate reasoning procedures. With different approximate reasoning algorithms discussed and developed in the literature, it needs to be clarified how these approaches can be compared, i.e. what it means that one approximate reasoning approach is better than some other. In this paper, we will formally define such a foundation for approximate reasoning research. We will clarify -- by means of notions from statistics -- how different approximate algorithms can be compared, and ground the most fundamental notions in the field formally. We will also exemplify what a corresponding statistical comparison of algorithms would look like. - Forschungsgruppe:Research Group: Computational LogicComputational Logic
@techreport{RTH2008,
author = {Sebastian Rudolph and Tuvshintur Tserendorj and Pascal Hitzler},
title = {What Is Approximate Reasoning?},
institution = {Institute {AIFB,} University of Karlsruhe},
year = {2008},
month = {March}
}
