Query Cache: Adaptive SPARQL Query Cache

In order to get closer to the performance of relational database-backed Web applications, we developed an approach for improving the performance of triple stores by caching query results and even complete application objects. The selective invalidation of cache objects, following updates of the underlying knowledge bases, is based on analysing the graph patterns of cached SPARQL queries in order to obtain information about what kind of updates will change the query result.

Project Team

Former Members

News

AKSW Colloquium, 28.11.2016, NED using PBOH + Large-Scale Learning of Relation-Extraction Rules. ( 2016-11-26T12:30:29+01:00 by Diego Moussallem)

2016-11-26T12:30:29+01:00 by Diego Moussallem

In the upcoming Colloquium, November the 28th at 3 PM, two papers will be presented: Probabilistic Bag-Of-Hyperlinks Model for Entity Linking Diego Moussallem will discuss the paper “Probabilistic Bag-Of-Hyperlinks Model for Entity Linking” by Octavian-Eugen Ganea et. al. Read more about "AKSW Colloquium, 28.11.2016, NED using PBOH + Large-Scale Learning of Relation-Extraction Rules."

Accepted paper in AAAI 2017 ( 2016-11-14T14:48:46+01:00 by Mohamed Sherif)

2016-11-14T14:48:46+01:00 by Mohamed Sherif

Hello Community! Read more about "Accepted paper in AAAI 2017"

AKSW Colloquium, 17.10.2016, Version Control for RDF Triple Stores + NEED4Tweet ( 2016-10-17T09:55:50+02:00 by Marvin Frommhold)

2016-10-17T09:55:50+02:00 by Marvin Frommhold

In the upcoming Colloquium, October the 17th at 3 PM, two papers will be presented: Version Control for RDF Triple Stores Marvin Frommhold will discuss the paper “Version Control for RDF Triple Stores” by Steve Cassidy and James Ballantine which forms the foundation … Continue reading → Read more about "AKSW Colloquium, 17.10.2016, Version Control for RDF Triple Stores + NEED4Tweet"

LIMES 1.0.0 Released ( 2016-10-14T11:38:31+02:00 by Kleanthi Georgala)

2016-10-14T11:38:31+02:00 by Kleanthi Georgala

Dear all, the LIMES Dev team is happy to announce LIMES 1.0.0. LIMES, the Link Discovery Framework for Metric Spaces, is a link discovery framework for the Web of Data. Read more about "LIMES 1.0.0 Released"

DL-Learner 1.3 (Supervised Structured Machine Learning Framework) Released ( 2016-10-11T21:41:00+02:00 by Dr. Jens Lehmann)

2016-10-11T21:41:00+02:00 by Dr. Jens Lehmann

Dear all, the Smart Data Analytics group at AKSW is happy to announce DL-Learner 1.3. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.3 (Supervised Structured Machine Learning Framework) Released"