TY  - JOUR
A1  - Verborgh, Ruben
A1  - Vander Sande, Miel
A1  - Hartig, Olaf
A1  - Van Herwegen, Joachim
A1  - De Vocht, Laurens
A1  - De Meester, Ben
A1  - Haesendonck, Gerald
A1  - Colpaert, Pieter
T1  - Triple Pattern Fragments: A low-cost knowledge graph interface for the Web
JF  - Web semantics : science, services and agents on the World Wide Web
N2  - Billions of Linked Data triples exist in thousands of RDF knowledge graphs on the Web, but few of those graphs can be queried live from Web applications. Only a limited number of knowledge graphs are available in a queryable interface, and existing interfaces can be expensive to host at high availability. To mitigate this shortage of live queryable Linked Data, we designed a low-cost Triple Pattern Fragments interface for servers, and a client-side algorithm that evaluates SPARQL queries against this interface. This article describes the Linked Data Fragments framework to analyze Web interfaces to Linked Data and uses this framework as a basis to define Triple Pattern Fragments. We describe client-side querying for single knowledge graphs and federations thereof. Our evaluation verifies that this technique reduces server load and increases caching effectiveness, which leads to lower costs to maintain high server availability. These benefits come at the expense of increased bandwidth and slower, but more stable query execution times. These results substantiate the claim that lightweight interfaces can lower the cost for knowledge publishers compared to more expressive endpoints, while enabling applications to query the publishers’ data with the necessary reliability.
KW  - Linked Data
KW  - Linked Data Fragments
KW  - Querying
KW  - SPARQL
Y1  - 2016
U6  - https://doi.org/10.1016/j.websem.2016.03.003
SN  - 1570-8268
VL  - 37-38
SP  - 184
EP  - 206
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - BOOK
A1  - Lange, Dustin
A1  - Böhm, Christoph
A1  - Naumann, Felix
T1  - Extracting structured information from Wikipedia articles to populate infoboxes
N2  - Roughly every third Wikipedia article contains an infobox - a table that displays important facts about the subject in attribute-value form. The schema of an infobox, i.e., the attributes that can be expressed for a concept, is defined by an infobox template. Often, authors do not specify all template attributes, resulting in incomplete infoboxes. With iPopulator, we introduce a system that automatically populates infoboxes of Wikipedia articles by extracting attribute values from the article's text. In contrast to prior work, iPopulator detects and exploits the structure of attribute values for independently extracting value parts. We have tested iPopulator on the entire set of infobox templates and provide a detailed analysis of its effectiveness. For instance, we achieve an average extraction precision of 91% for 1,727 distinct infobox template attributes.
N2  - Ungefähr jeder dritte Wikipedia-Artikel enthält eine Infobox - eine Tabelle, die wichtige Fakten über das beschriebene Thema in Attribut-Wert-Form darstellt. Das Schema einer Infobox, d.h. die Attribute, die für ein Konzept verwendet werden können, wird durch ein Infobox-Template definiert. Häufig geben Autoren nicht für alle Template-Attribute Werte an, wodurch unvollständige Infoboxen entstehen. Mit iPopulator stellen wir ein System vor, welches automatisch Infoboxen von Wikipedia-Artikeln durch Extrahieren von Attributwerten aus dem Artikeltext befüllt. Im Unterschied zu früheren Arbeiten erkennt iPopulator die Struktur von Attributwerten und nutzt diese aus, um die einzelnen Bestandteile von Attributwerten unabhängig voneinander zu extrahieren. Wir haben iPopulator auf der gesamten Menge der Infobox-Templates getestet und analysieren detailliert die Effektivität. Wir erreichen beispielsweise für die Extraktion einen durchschnittlichen Precision-Wert von 91% für 1.727 verschiedene Infobox-Template-Attribute.
T3  - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 38 
KW  - Informationsextraktion
KW  - Wikipedia
KW  - Linked Data
KW  - Information Extraction
KW  - Wikipedia
KW  - Linked Data
Y1  - 2010
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-45714
SN  - 978-3-86956-081-6
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  -