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4th International Conference on knowledge engineering and semantic web, KESW 2013

作者： Höffner, Konrad Unger, Christina Bühmann, Lorenz Lehmann, Jens Ngonga Ngomo, Axel-Cyrille Gerber, Daniel Cimiano, Phillip Agile Knowledge Engineering and Semantic Web Institute of Computer Science Universitty of Leipzig Germany

ISBN: (纸本)9783642413599

As an increasing amount of RDF data is published as Linked Data, intuitive ways of accessing this data become more and more important. Natural language question answering approaches have been proposed as a good compromise between intuitiveness and expressiveness. We present a user interface for the template based question answering system which covers the full question answering pipeline and answers factual questions with a list of RDF resources. Users can ask full-sentence, English factual questions and get a list of resources which are then visualized using those properties which are expected to carry the most important information for the user. The available knowledge bases are (1) DBpedia for general domain question answering and (2) Oxford real estate for housing searches. However, the system is easily extensible to other knowledge bases. © Springer-Verlag Berlin Heidelberg 2013.

关键词： User interfaces

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Inference of latent shape expressions associated to DBpedia ontology

Inference of latent shape expressions associated to DBpedia ...

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2018 ISWC Posters and Demonstrations, Industry and Blue Sky Ideas Tracks, ISWC-P and D-Industry-BlueSky 2018

作者： Fernández-Álvarez, Daniel García-González, Herminio Frey, Johannes Hellmann, Sebastian Gayo, José Emilio Labra Department of Computer Science University of Oviedo Oviedo33007 Spain Agile Knowledge Engineering Semantic Web University of Leipzig Leipzig04109 Germany

In order to perform any operation in an RDF graph, it is recommendable to know the expected topology of the targeted information. Some technologies have been developed in the last years to describe the expected shapes in an RDF graph, such as ShEx or SHACL. In general, a domain expert can define the expected shapes in a graph, but there are some scenarios in which the schema cannot be predicted a priori, but it emerges at the same time that the graph is filled with new information (the shapes are latent). We have developed a prototype which is able to infer shapes of classes in a knowledge graph and used it with classes of DBpedia ontology. We serialize our results using ShEx. © 2018 CEUR-WS. All rights reserved.

关键词： Ontology

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Adding semantics to Social Software engineering: (Re-)Using Ontologies in a Community-oriented Requirements engineering Environment

Adding Semantics to Social Software Engineering: (Re-)Using ...

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2010 Workshopband (inkl.Doktorandensymposium), Fachtagung des GI-Fachbereichs Softwaretechnik, Software engineering 2010 - 2010 Workshop (incl. Doctoral Symposium), Conference of the GI Division on Software engineering, Software engineering 2010

作者： Lohmann, Steffen Riechert, Thomas DEI Laboratory Computer Science Department Carlos III University of Madrid Spain Agile Knowledge Engineering and Semantic Web Department of Computer Science University of Leipzig Germany

ISBN: (纸本)9783885792543

Social Software is typically characterized by low formal semantics and weakly structured contents. Software engineering, in contrast, requires at least a certain degree of formality and structure. In order to face these opposing demands, we propose to ground Social Software engineering on concepts and technologies from the semantic web. In particular, we present a semantic Wiki based approach in this paper that uses well-known ontologies to represent activities and artifacts that emerge in an online environment for community-oriented Requirements engineering. We illustrate the benefits of reusing these domain-independent ontologies and show how they can fruitfully be combined and interlinked in one common upper ontology. © 2010 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Ontology

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A web Platform for Social Requirements engineering

A Web Platform for Social Requirements Engineering

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2009 Workshopband, Fachtagung des GI-Fachbereichs Softwaretechnik, Software engineering 2009 - 2009 Workshop Conference of the GI Division on Software engineering, Software engineering 2009

作者： Lohmann, Steffen Dietzold, Sebastian Heim, Philipp Heino, Norman Interactive Systems and Interaction Design University of Duisburg-Essen Lotharstrasse 65 Duisburg45057 Germany Agile Knowledge Engineering and Semantic Web University of Leipzig Johannisgasse 26 Leipzig04009 Germany

ISBN: (纸本)9783885792444

This paper presents a web platform that applies concepts from the domain of Social Software to requirements engineering. The platform implements several community-oriented features that support collaboration and knowledge sharing and aim to foster the engagement of larger groups of stakeholders in the collection, discussion, development, and structuring of software requirements. © 2009 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Social software

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Towards versioning of arbitrary RDF data 2016

Towards versioning of arbitrary RDF data

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12th International Conference on semantic Systems, semanticS 2016

作者： Frommhold, Marvin Piris, Rubén Navarro Arndt, Natanael Tramp, Sebastian Petersen, Niklas Martin, Michael Agile Knowledge Engineering and Semantic Web Institute of Computer Science University of Leipzig Germany eccenca GmbH Hainstr. 8 Leipzig04109 Germany Enterprise Information Systems Institute for Applied Computer Science University of Bonn Germany

ISBN: (纸本)9781450347525

Coherent and consistent tracking of provenance data and in particular update history information is a crucial building block for any serious information system architecture. Version Control Systems can be a part of such an architecture enabling users to query and manipulate versioning information as well as content revisions. In this paper, we introduce an RDF versioning approach as a foundation for a full featured RDF Version Control System. We argue that such a system needs support for all concepts of the RDF specification including support for RDF datasets and blank nodes. Furthermore, we placed special emphasis on the protection against unperceived history manipulation by hashing the resulting patches. In addition to the conceptual analysis and an RDF vocabulary for representing versioning information, we present a mature implementation which captures versioning information for changes to arbitrary RDF datasets. © 2016 Copyright held by the owner/author(s).

关键词： Resource Description Framework (RDF)

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SPARQL as a foreign language 13

SPARQL as a foreign language

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Posters and Demos Track of the 13th International Conference on semantic Systems semanticS, SEMPDS 2017

作者： Soru, Tommaso Marx, Edgard Moussallem, Diego Publio, Gustavo Valdestilhas, André Esteves, Diego Neto, Ciro Baron Agile Knowledge Engineering and Semantic Web Institute of Computer Science University of Leipzig Germany Faculty of Computer Science Mathematics and Natural Sciences Leipzig University of Applied Sciences Germany Smart Data Analytics University of Bonn Germany

Recently, the Linked Data Cloud has achieved a size of more than 100 billion facts pertaining to a multitude of domains. However, accessing this information has been significantly challenging for lay users. Approaches to problems such as Question Answering on Linked Data and Link Discovery have notably played a role in increasing information access. These approaches are often based on handcrafted and/or statistical models derived from data observation. Recently, Deep Learning architectures based on Neural Networks called seq2seq have shown to achieve the state-of-the-art results at translating sequences into sequences. In this direction, we propose Neural SPARQL Machines, end-to-end deep architectures to translate any natural language expression into sentences encoding SPARQL queries. Our preliminary results, restricted on selected DBpedia classes, show that Neural SPARQL Machines are a promising approach for Question Answering on Linked Data, as they can deal with known problems such as vocabulary mismatch and perform graph pattern composition. � 2018 CEUR-WS. All rights reserved.

关键词： Linked data

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LargeRDFBench: A Billion Triples Benchmark for SPARQL Endpoint Federation

SSRN

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SSRN 2018年

作者： Saleema, Muhammad Hasnain, Ali Ngomo, Axel-Cyrille Ngonga Universität Leipzig IFI Agile Knowledge Engineering and Semantic Web AKSW PO 100920 LeipzigD-04009 Germany Insight Centre for Data Analytics National University of Ireland Galway Ireland

Gathering information from the distributed web of Data is commonly carried out by using SPARQL query federation approaches. However, the fitness of current SPARQL query federation approaches for real applications is difficult to evaluate with current benchmarks as they are either synthetic, too small in size and complexity or do not provide means for a fine-grained evaluation. We propose LargeRDFBench, a billion-triple benchmark for SPARQL query federation which encompasses real data as well as real queries pertaining to real bio-medical use cases. We evaluate state-of-the-art SPARQL endpoint federation approaches on this benchmark with respect to their query runtime, triple pattern-wise source selection, number of endpoints requests, and result completeness and correctness. Our evaluation results suggest that the performance of current SPARQL query federation systems on simple queries (in terms of total triple patterns, query result set sizes, execution time, use of SPARQL features etc.) does not reflect the systems' performance on more complex queries. Moreover, current federation systems seem unable to deal with real queries that involve processing large intermediate result sets or lead to large result sets. © 2018, The Authors. All rights reserved.

关键词： Query processing

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Preface

OpenAccess Series in Informatics

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OpenAccess Series in Informatics 2019年 70卷 IX-X页

作者： Eskevich, Maria de Melo, Gerard Fäth, Christian McCrae, John P. Buitelaar, Paul Chiarcos, Christian Klimek, Bettina Dojchinovski, Milan CLARIN ERIC Utrecht Netherlands Department of Computer Science Rutgers University New BrunswickNJ United States Applied Computational Linguistics Goethe University Frankfurt Germany Insight Centre for Data Analytics National University of Ireland Galway Ireland Agile Knowledge Engineering and Semantic Web University of Leipzig Germany

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Development of a Novel Chemoinformatic Tool for Natural Product Databases

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Future Drug Discovery 2023年第2期5卷

作者： Paulo Ricardo Viviurka do Carmo Ricardo Marcacini Marilia Valli João Victor Silva-Silva Leonardo Luiz Gomes Ferreira Alan Cesar Pilon Vanderlan da Silva Bolzani Adriano D Andricopulo Edgard Marx 1 Agile Knowledge Engineering & Semantic Web (AKSW) Institute of Computer Science Leipzig University Leipzig04109 Germany 2 Computer Science & Mathematics Institute University of São Paulo São Carlos SP13566-590 Brazil 3 Laboratory of Medicinal & Computational Chemistry São Carlos Institute of Physics University of São Paulo São Carlos SP13563-120 Brazil 4 Nuclei of Bioassays Biosynthesis & Ecophysiology of Natural Products (NuBBE) Department of Organic Chemistry Institute of Chemistry São Paulo State University (UNESP) Araraquara SP14800-901 Brazil

Aim:This study aimed to develop a chemoinformatic tool for extracting natural product information from academic *** & methods:Machine learning graph embeddings were used to extract knowledge from a knowledge graph, connecting properties, molecular data and BERTopic ***:Metapath2Vec performed best in extracting compound names and showed improvement over evaluation stages. Embedding Propagation on Heterogeneous Networks achieved the best performance in extracting bioactivity information. Metapath2Vec excelled in extracting species information, while DeepWalk and Node2Vec performed well in one stage for species location extraction. Embedding Propagation on Heterogeneous Networks consistently improved performance and achieved the best overall scores. Unsupervised embeddings effectively extracted knowledge, with different methods excelling in different ***:This research establishes a foundation for frameworks in knowledge extraction, benefiting sustainable resource *** language summaryIn this study, a tool to extract relevant information on natural products from scientific papers was developed. Advanced machine learning techniques were used to create a knowledge graph by connecting different information sources. Several methods were tested, with some showing better performance in specific tasks such as the extraction of compound names and bioactivity information. The incorporation of additional data associated with the studied resources proved to improve the results of the models. This study provides a foundation for the development of future tools that can assist researchers in extracting valuable knowledge from scientific literature. Such tools have the potential to facilitate drug discovery efforts and promote the sustainable utilization of natural resources.

关键词： chemoinformatics databases drug discovery knowledge extraction knowledge graphs machine learning natural products NuBBEDB

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