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DBpedia is a huge dataset essentially extracted from the content and structure of Wikipedia. We present a new extraction producing a linked data representation of the editing history of Wikipedia pages. This supports custom querying and combining with other data providing new indicators and insights. We explain the architecture, representation and an immediate application to monitoring events.
More than a billion users on the Web are on social networks sharing and consuming short and real-time updates. Consumers of social data face information overload. Although information filtering can help, challenges that are specific to the short-text and real-time nature of social networks must be addressed. Knowledge bases -- particularly those derived from crowd-sourced platforms such as Wikipedia...
Many web resources require an accurate representation of family relationships. However, available ontologies describing this kind of relationships provide only simple and rudimentary representations. In addition, the transition from one culture/language to another cannot be solved with simple translation solutions, specifically when concepts do not intersect in different cultures. In this paper, we...
This paper describes Qsense — an educational and research Web application, developed to ease the interrogation of DBpedia for users intending to learn the most important concepts regarding the Semantic Web, especially to increase the knowledge about DBpedia in a pragmatic way. Additionally, by providing a compelling Web interface, Qsense offers the possibility to explore the DBpedia's ontology structure...
The World Wide Web (WWW) has radically changed the way in which we access, generate and disseminate information. Its presence is felt daily and with more internet-enabled devices being connected the web of knowledge is growing. We are now moving into era where the WWW is capable of ‘understanding’ the actual/intended meaning of our content. This is being achieved by creating links between distributed...
The development of modern health care and clinical practice increase the need of nutritional and medical data extraction and integration across heterogeneous data sources. It can be useful for researchers and patients if there is a way to extract relevant information and organize it as easily shared and machine-processable linked data. In this paper, we describe an automatic approach that extracts...
This paper presents a commercial semantic-based system for the Romanian tourism. The Lela system exploits both open linked data from Romanian and international sources, and also proprietary databases in the tourism domain. We present the process of creating the linked data set, based on: i) engineering the LELA Romanian tourism ontology, and ii) populating the ontology by linking open data. The system...
With the growing amount of published RDF datasets on similar domains, data conflict between similar entities (same-as) is becoming a common problem for Web of Data applications. In this paper we propose an algorithm to detect conflict of same properties values of similar entities and select the most accurate value. The proposed algorithm contains two major steps. The first step filters out low ranked...
The Web's promise for planet-scale data integration depends on solving the thorny problem of identity: given one or more possible identifiers, how can we determine whether they refer to the same or different things? Here, the authors discuss various ways to deal with the identity problem in the context of linked data.
Currently the user's web search is disjoint from the resources which is subsequently browsed. Specifically the related instances of the search are not displayed on the following pages. This lack of continuity between the actual search and the web sites displayed may lead to skimming by the user to identify what is relevant on the pages. This paper presents an approach to the continuous modeling of...
Scientific data stands to represent a significant portion of the linked open data cloud and science itself stands to benefit from the data fusion capability that this will afford. However, simply publishing linked data into the cloud does not necessarily meet the requirements of reuse. Publishing has requirements of provenance, quality, credit, attribution, methods in order to provide the reproducibility...
This paper presents the concept of Interactive Relationship Discovery (IRD) and illustrates its application potentials in technology enhanced learning. Datasets of the Semantic Web are exploited to support learners in understanding how things are related. The approach is based on a user-oriented process model that has been implemented in an easy-to-use tool. A particular emphasis is on the interactive...
The efforts of publishing and interlinking structured data on the Semantic Web will result in a global network of databases, or the Linked Data, which provides huge potential for discovering hidden relationships. We present a multi-agent framework for Semantic Associations Discovery (SAD) from distributed linked data on the Semantic Web. Here, agents collaborate in SAD by publishing inter-dependent...
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