Saturday, November 22, 2014

Preprint: Mining Various Semantic Relationships from Unstructured User-Generated Web Data



Pei-Ling Hsu, Hsiao-Shan Hsieh, Jheng-He Liang and Yi-Shin Chen, Mining Various Semantic Relationships from Unstructured User-Generated Web Data, Web Semantics: Science, Services and Agents on the World Wide Web, to appear.

Absract: With the emergence of Web 2.0, the amount of user-generated web data has sharply increased. Thus, many studies have proposed techniques to extract wisdom from these user-generated datasets. Some of these works have focused on extracting semantic relationships through the use of search logs or social annotations, but only hierarchical relationships have been considered. The goal of this paper is to detect various semantic relationships (hierarchical and non-hierarchical) between concepts using search logs and social annotations. The experimental results demonstrate that our proposed approach constructs adequate relationships.

Friday, November 21, 2014

Preprint: On the Formulation of Performant SPARQL Queries



Antonis Loizou, Renzo Angles and Paul Groth, On the Formulation of Performant SPARQL Queries, Web Semantics: Science, Services and Agents on the World Wide Web, to appear.

Abstract: The combination of the flexibility of RDF and the expressiveness of SPARQL provides a powerful mechanism to model, integrate and query data. However, these properties also mean that it is nontrivial to write performant SPARQL queries. Indeed, it is quite easy to create queries that tax even the most optimised triple stores. Currently, application developers have little concrete guidance on how to write "good" queries. The goal of this paper is to begin to bridge this gap. It describes five heuristics that can be applied to create optimised queries. The heuristics are informed by formal results in the literature on the semantics and complexity of evaluating SPARQL queries, which ensures that queries following these rules can be optimised effectively by an underlying RDF store. Moreover, we empirically verify the ecacy of the heuristics using a set of openly available datasets and corresponding SPARQL queries developed by a large pharmacology data integration project. The experimental results show improvements in performance across six state-of-the-art RDF stores.

Wednesday, September 24, 2014

Preprint: Lessons Learnt from the Deployment of a Semantic Virtual Research Environment



Peter Edwards, Edoardo Pignotti, Chris Mellish, Alan Eckhardt, Kapila Ponnamperuma, Thomas Bouttaz, Lorna Philip, Kate Pangbourne, Gary Polhill and Nick Gotts, Lessons Learnt from the Deployment of a Semantic Virtual Research Environment, Web Semantics: Science, Services and Agents on the World Wide Web, to appear.


The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups.

Tuesday, September 23, 2014

CFP: Special Issue on Knowledge Graphs


JWS Special Issue on Knowledge Graphs


The Journal of Web Semantics invites submissions to a special issue on Knowledge Graphs to be edited by Markus Kroetzsch and Gerhard Weikum. Submissions are due by 28 February 2015.

Knowledge graphs are large networks of entities, their semantic types, properties, and relationships between entities. They have become a powerful asset for search, analytics, recommendations, and data integration. Rooted in academic research and community projects such as DBpedia, Freebase, Yago, BabelNet, ConceptNet, Nell, Wikidata, WikiTaxonomy, and others, knowledge graphs are now intensively used at big industrial stakeholders. Examples are the Google Knowledge Graph, Facebook's Graph Search, Microsoft Satori, Yahoo Knowledge, as well as thematically specialized knowledge bases in business, finance, life sciences and more. Many of these knowledge sources are available as Linked Open Data or RDF exports.

The goal of this special issue is to provide a stage for research on recent advances in knowledge graphs and their underlying semantic technologies. Traditional challenges of scalability, information quality, and data integration are of interest, but also specific projects that publish, study, or use knowledge graphs in innovative ways. More specifically, we expect submissions on (but not restricted to) the following topics.
  • Creation and curation of knowledge graphs
    • Automatic and semi-automatic creation of knowledge graphs
    • Data integration, disambiguation, schema alignment
    • Collaborative management of knowledge graphs
    • Quality control: noisy data, uncertainty, incomplete information
    • New kinds of knowledge graphs: common-sense, visual knowledge, etc.
  • Management and querying of knowledge graphs
    • Architectures for managing big graphs
    • Expressive query answering
    • Reasoning with large-scale, dynamic data
    • Data dynamics, update, and synchronization
    • Synthetic graphs and graph benchmarks
  • Applications of knowledge graphs
    • Innovative uses of knowledge graphs
    • Understanding and analyzing knowledge graphs
    • Semantic search
    • Question answering
    • Combining knowledge graphs with other information resources

Guest Editors

  • Markus Kroetzsch (primary contact), TU Dresden, markus.kroetzsch@tu-dresden.de
  • Gerhard Weikum, Max Planck Institute for Informatics, weikum@mpi-inf.mpg.de

Important Dates

We will aim at an efficient publication cycle in order to guarantee prompt availability of the published results. We will review papers on a rolling basis as they are submitted and explicitly encourage submissions well before the submission deadline. Submit papers online at the journal's Elsevier Web site.
  • Submission deadline: 28 February 2015
  • Author notification: 31 May 2015
  • Final version: 31 July 2015
  • Final notification: 31 October 2015
  • Publication: late 2015/early 2016

Submission guidelines

The Journal of Web Semantics solicits original scientific contributions of high quality. Following the overall mission of the journal, we emphasize the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services.

Submission of your manuscript is welcome provided that it, or any translation of it, has not been copyrighted or published and is not being submitted for publication elsewhere. Manuscripts should be prepared for publication in accordance with instructions given in the JWS guide for authors. The submission and review process will be carried out using Elsevier's Web-based EES system. To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important that authors select "S.I.: Knowledge Graphs" at the "Article Type" step in the submission process.

Upon acceptance of an article, the author(s) will be asked to transfer copyright of the article to the publisher. This transfer will ensure the widest possible dissemination of information. Elsevier's liberal preprint policy permits authors and their institutions to host preprints on their web sites. Preprints of the articles will be made freely accessible on the JWS preprint server. Final copies of accepted publications will appear in print and at Elsevier's archival online server.

Friday, September 19, 2014

CFP: Special Issue on Geospatial Semantics


Special Issue of the JWS on Geospatial Semantics


The Journal of Web Semantics seeks submissions for a special issue on geospatial semantics to be edited by Yolanda Gil and Raphaël Troncy. Submissions are due by January 31, 2015.

Geospatial reasoning has an increasingly larger scope in the semantic web. More and more information is geolocated, more mobile devices produce geocoded records, and more web mashups are created to convey geospatial information. Semantics can enable automated integration of geospatial information, and track the provenance of the data shown to an end user. Semantics can also improve visualizations and querying of geospatial data. Semantics can also support crowdsourcing of geospatial data, particularly to track identity through name and property changes over time. Several recent workshops on geospatial semantics have emphasized the interest in the community on these topics. Of note are workshops organized by the World Wide Web Consortium (W3C) and the Open Geospatial Consortium (OGC) indicating a strong interest in standardization efforts in geospatial semantics. This special issue aims to synthesize the recent trends in research and practice in the area of geospatial semantics.

Topics of interest include but are not limited to:
  • Combining semantic information with more traditional representations and standards for geospatial data
  • Exploiting semantics to enhance visualizations of geospatial information
  • Use of semantics to support geospatial data integration and conflation
  • Semantic mashups of geospatial data
  • Semantic provenance of geospatial data (e.g., PROV)
  • Semantics for mobile geospatial applications
  • Geospatial linked open data
  • Managing privacy of personal geospatial data and whereabouts through semantics
  • Combining semantic web standards (W3C) with geospatial (OGC) standards (e.g., GML)
  • Format for representing geographical data (e.g., GeoJSON)
  • Semantics for crowdsourcing geospatial information
  • Semantics for exploiting geospatial information in social network platforms
  • Scalable reasoning with semantic geospatial data
  • Real world applications of semantic geospatial frameworks

Guest Editors

  • Yolanda Gil, Information Sciences Institute, University of Southern California
  • Raphaël Troncy, Multimedia Communications Department, EURECOM

Important Dates

  • Call for papers: September 20, 2014
  • Submission deadline: January 31, 2015
  • Author notification: mid-April 2015
  • Publication: third quarter of 2015

Submission guidelines

The Journal of Web Semantics solicits original scientific contributions of high quality. Following the overall mission of the journal, we emphasize the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services.

Submission of your manuscript is welcome provided that it, or any translation of it, has not been copyrighted or published and is not being submitted for publication elsewhere. Manuscripts should be prepared for publication in accordance with instructions given in the JWS guide for authors. The submission and review process will be carried out using Elsevier's Web-based EES system. Upon acceptance of an article, the author(s) will be asked to transfer copyright of the article to the publisher. This transfer will ensure the widest possible dissemination of information. Elsevier's liberal preprint policy permits authors and their institutions to host preprints on their web sites. Preprints of the articles will be made freely accessible on the JWS preprint server. Final copies of accepted publications will appear in print and at Elsevier's archival online server.

Wednesday, September 3, 2014

Preprint: SINA: Semantic Interpretation of User Queries for Question Answering on Interlinked Data



Saeedeh Shekarpour, Edgard Marx, Axel-Cyrille Ngonga Ngomo and Sören Auer, SINA: Semantic Interpretation of User Queries for Question Answering on Interlinked Data, Web Semantics: Science, Services and Agents on the World Wide Web, to appear.

Abstract: The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.

Monday, September 1, 2014

Preprint: Global Machine Learning for Spatial Ontology Population, Kordjamshidi and Moens


Parisa Kordjamshidi and Marie-Francine Moens, Global Machine Learning for Spatial Ontology Population, Web Semantics: Science, Services and Agents on the World Wide Web, to appear. 

Abstract: Understanding spatial language is important in many applications such as geographical information systems, human computer interaction or text-to-scene conversion. Due to the challenges of designing spatial ontologies, the extraction of spatial information from natural language still has to be placed in a well-defined framework. In this work, we propose an ontology which bridges between cognitive-linguistic spatial concepts in natural language and multiple qualitative spatial representation and reasoning models. To make a mapping between natural language and the spatial ontology, we propose a novel global machine learning framework for ontology population. In this framework we consider relational features and background knowledge which originates from both ontological relationships between the concepts and the structure of the spatial language. The advantage of the proposed global learning model is the scalability of the inference, and the flexibility for automatically describing text with arbitrary semantic labels that form a structured ontological representation of its content. The machine learning framework is evaluated with SemEval-2012 and SemEval-2013 data from the spatial role labeling task.

Thursday, August 28, 2014

Preprint: Theophrastus: On Demand and Real-Time Automatic Annotation and Exploration of (Web) Documents using Open Linked Data


Pavlos Fafalios and Panagiotis Papadakos, Theophrastus: On Demand and Real-Time Automatic Annotation and Exploration of (Web) Documents using Open Linked Data, Web Semantics: Science, Services and Agents on the World Wide Web, to appear.

Abstract: Theophrastus is a system that supports the automatic annotation of (Web) documents through entity mining and provides exploration services by exploiting Linked Open Data (LOD), in real-time and only when needed. The system aims at assisting biologists in their research on species and biodiversity. It was based on requirements coming from the biodiversity domain and was awarded the first prize in the Blue Hackathon 2013. Theophrastus has been designed to be highly configurable regarding a number of different aspects like entities of interest, information cards and external search systems. As a result it can be exploited in different contexts and other areas of interest. The provided experimental results show that the proposed approach is efficient and can be applied in real-time.