Efficient Optimization and Processing of Queries over Text-rich Graph-structured Data

Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art

Gimme The Context: Context-driven automatic semantic annotation with C-PANKOW

Cimiano P, Ladwig G, Staab S. Gimme The Context: Context-driven automatic semantic annotation with C-PANKOW. In: Ellis A, Hagino T, eds. Proceedings of the 14th international conference on World Wide Web, WWW 2005. ACM Press; 2005: 332-341

Generating and visualizing a soccer knowledge base

This demo abstract describes the SmartWeb Ontology-based Information Extraction System (SOBIE). A key feature of SOBIE is that all information is extracted and stored with respect to the SmartWeb ontology. In this way, other components of the systems, which use the same ontology, can access this information in a straightforward way. We will show how information extracted by SOBIE is visualized within its original context, thus enhancing the browsing experience of the end user

A Distributed Graph Approach for Pre-processing Linked RDF Data Using Supercomputers

Efficient RDF, graph based queries are becoming more pertinent based on the increased interest in data analytics and its intersection with large, unstructured but connected data. Many commercial systems have adopted distributed RDF graph systems in order to handle increasing dataset sizes and complex queries. This paper introduces a distribute graph approach to pre-processing linked data. Instead of traversing the memory graph, our system indexes pre-processed join elements that are organized in a graph structure. We analyze the Dbpedia data-set (derived from the Wikipedia corpus) and compare our access method to the graph traversal access approach which we also devise. Results show from our experiments that the distributed, pre-processed graph approach to accessing linked data is faster than the traversal approach over a specific range of linked queries

SmartWeb: Mobile Access to the Semantic Web

Ankolekar A, Cimiano P, Hitzler P, et al. SmartWeb: Mobile Access to the Semantic Web. In: Wache H, ed. Proceedings of the ESWC2006 poster and demo session. 2006: 3-4

Efficient Optimization and Processing of Queries over Text-rich Graph-structured Data

Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art

Corpus-based Pattern Induction for a Knowledge-based Question Answering Approach

Cimiano P, Erdmann M, Ladwig G. Corpus-based Pattern Induction for a Knowledge-based Question Answering Approach. In: Proceedings of the First IEEE International Conference on Semantic Computing (ICSC 2007). IEEE Computer Society; 2007: 671-678.In this paper, we present an approach which, given a knowledge base and an appropriate text corpus, automatically induces patterns which can be used to query the knowledge base. We do not only consider simple questions but text problems consisting of several sentences. Answers to complex text problems are determined by an inference process which computes the answer on the basis of the background knowledge in the knowledge base (KB) as well as the textual description of the problem. The question formulated in natural language thus needs to be translated into appropriate KB structures and queries. Our approach to translating the natural language question uses an underlying corpus and the knowledge base to derive meaningful and relevant patterns which can then be used to process the questions and capture their meaning with respect to the underlying knowledge base. We apply our approach to advanced placement (AP) questions in three areas: physics, chemistry and biology. We report results of a first evaluation of the translation procedure for the three domains