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- Sairam Gurajada, Stephan Seufert, Iris Miliaraki, Martin Theobald
- SIGMOD Conference
- 2014

We investigate a new approach to the design of distributed, shared-nothing RDF engines. Our engine, coined "TriAD", combines join-ahead pruning via a novel form of RDF graph summarization with a locality-based, horizontal partitioning of RDF triples into a grid-like, distributed index structure. The multi-threaded and distributed execution of joins in TriAD… (More)

Computing shortest paths between two given nodes is a fundamental operation over graphs, but known to be nontrivial over large disk-resident instances of graph data. While a number of techniques exist for answering reachability queries and approximating node distances efficiently, determining actual shortest paths (i.e. the sequence of nodes involved) is… (More)

Measuring the semantic relatedness between two entities is the basis for numerous tasks in IR, NLP, and Web-based knowledge extraction. This paper focuses on disambiguating names in a Web or text document by jointly mapping all names onto semantically related entities registered in a knowledge base. To this end, we have developed a novel notion of semantic… (More)

- Stephan Seufert, Avishek Anand, Srikanta J. Bedathur, Gerhard Weikum
- 2013 IEEE 29th International Conference on Data…
- 2013

In this paper, we propose a scalable and highly efficient index structure for the reachability problem over graphs. We build on the well-known node interval labeling scheme where the set of vertices reachable from a particular node is compactly encoded as a collection of node identifier ranges. We impose an explicit bound on the size of the index and… (More)

We study how to automatically extract tourist trips from large volumes of geo-tagged photographs. Working with more than 8 million of these photographs that are publicly available via photo- sharing communities such as Flickr and Panoramio, our goal is to satisfy the needs of a tourist who specifies a starting location (typically a hotel) together with a… (More)

- Andrey Gubichev, Srikanta J. Bedathur, Stephan Seufert
- GRADES
- 2013

As Semantic Web efforts continue to gather steam, the RDF engines are faced with graphs with millions of nodes and billions of edges. While much recent work in addressing the resulting scalability issues in processing queries over these datasets have mainly considered SPARQL 1.0, the next-generation query language recommendations have proposed the addition… (More)

The need for scalable and efficient RDF stores has seen a high demand recently. Many efficient systems, both centralized and distributed, have been proposed. Since a row-oriented output is required by SPARQL, most of the current systems rely on relational joins. One of the problems with relational joins, though, is a performance bottleneck imposed by the… (More)

- Stephan Seufert, Srikanta J. Bedathur, Julián Mestre, Gerhard Weikum
- 2010 IEEE International Conference on Data Mining
- 2010

Graphs are increasingly used to model a variety of loosely structured data such as biological or social networks and entity-relationships. Given this profusion of large-scale graph data, efficiently discovering interesting substructures buried within is essential. These substructures are typically used in determining subsequent actions, such as conducting… (More)

In this work we introduced the label-constrained shortest path problem as an extension to the shortest path problem that allows a shortest path query to specify which edge labels are allowed on shortest paths. Furthermore we analyse its theoretical difficulty for exact indexing strategies and come to the conclusion that exact indexing is hard for graphs… (More)

In this paper, we propose a scalable and highly efficient index structure for the reachability problem over graphs. We build on the well-known node interval labeling scheme where the set of vertices reachable from a particular node is compactly encoded as a collection of node identifier ranges. We impose an explicit bound on the size of the index and… (More)