Beschreibung, Verarbeitung und Überprüfung Client-seitiger Security für SaaS gestützte Cloud Anwendungen

Datum

07.12.2017

Zeit

15:00 - 16:00

Sprecher

Dipl.-Ing. Jörg Kebbedies

Zugehörigkeit

Institut für Systemarchitektur, Lehrstuhl Rechnernetze

Sprache

en

Hauptthema

Informatik

Andere Themen

Informatik

Beschreibung

Probabilistic data and knowledge bases are becoming increasingly important in academia and industry. They are constantly extended with new data, powered by modern information extraction tools that associate probabilities with knowledge base facts. The state of the art to store and process such data is founded on probabilistic database systems, which are widely and successfully employed. Beyond all the success stories, however, such systems still lack the fundamental machinery to convey some of the valuable knowledge hidden in them to the end user, which limits their potential applications in practice. In particular, in their classical form, such systems are typically based on strong, unrealistic limitations, such as the closed-world assumption, the tuple-independence assumption, and the lack of commonsense knowledge. These limitations do not only lead to unwanted consequences, but also put such systems on weak footing in important tasks, querying answering being a very central one. In this thesis, we enhance probabilistic data and knowledge bases with more realistic data models, thereby allowing for better means for querying them. Building on the long endeavor of unifying logic and probability, we develop different rigorous semantics for probabilistic data and knowledge bases, analyze their computational properties and identify sources of in - tractability and design practical scalable query answering algorithms whenever possible. To achieve this, the current work brings together some recent paradigms from database theory and logic for probabilistic query answering and related inference tasks.

Letztmalig verändert: 07.12.2017, 08:38:26