Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  Lineage Enabled Query Answering in Uncertain Knowledge Bases

Iqbal, J. (2011). Lineage Enabled Query Answering in Uncertain Knowledge Bases. Master Thesis, Universität des Saarlandes, Saarbrücken.

Item is

Basisdaten

einblenden: ausblenden:
Genre: Hochschulschrift
Andere : Lineage-enabled Query Answering in Uncertain Knowledge Bases

Dateien

einblenden: Dateien
ausblenden: Dateien
:
2011_Javeria_Iqbal_Thesis.pdf (beliebiger Volltext), 1019KB
 
Datei-Permalink:
-
Name:
2011_Javeria_Iqbal_Thesis.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Eingeschränkt (Max Planck Institute for Informatics, MSIN; )
MIME-Typ / Prüfsumme:
application/pdf
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
-
Lizenz:
-

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Iqbal, Javeria1, 2, Autor           
Theobald, Martin2, Ratgeber           
Michel, Sebastian2, Gutachter           
Affiliations:
1International Max Planck Research School, MPI for Informatics, Max Planck Society, ou_1116551              
2Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: We present a unified framework for query answering over uncertain RDF knowledge bases. Specifically, our proposed design combines correlated base facts with a query driven, top down deductive grounding phase of first-order logic formulas (i.e., Horn rules) followed by a probabilistic inference phase. In addition to static input correlations among base facts, we employ the lineage structure obtained from processing the rules during grounding phase, in order to trace the logical dependencies of query answers (i.e., derived facts) back to the base facts. Thus, correlations (or more precisely: dependencies) among facts in a knowledge base may arise from two sources: 1) static input dependencies obtained from real-world observations; and 2) dynamic dependencies induced at query time by the rule-based lineage structure of the query answer. Our implementation employs state-of-the-art inference techniques: We apply exact inference whenever tractable, the detection of shared factors, shrink- age of Boolean formula when feasible, and Gibbs sampling in the general case. Our experiments are conducted on real data sets with synthetic expansion of correlated base facts. The experimental evaluation demonstrates the practical viability and scalability of our approach, achieving interactive query response times over a very large knowledge base. The experimental results provide the success guarantee of our presented framework.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2011-082011
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: Saarbrücken : Universität des Saarlandes
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: Iqbal2011
 Art des Abschluß: Master

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle

einblenden: