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Mobile cultural heritage guide: location-aware semantic search
"... Abstract. In this paper we explore the use of location aware mobile devices for searching and browsing a large number of general and cultural heritage information repositories. Based on GPS positioning we can determine a user’s location and context, composed of physical nearby locations, historic ev ..."
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Abstract. In this paper we explore the use of location aware mobile devices for searching and browsing a large number of general and cultural heritage information repositories. Based on GPS positioning we can determine a user’s location and context, composed of physical nearby locations, historic events that have taken place there, artworks that were created at or inspired by those locations and artists that have lived or worked there. Based on a geolocation, the user has three levels of refinement: pointing to a specific heading and selection and facets and subfacets of cultural heritage objects. In our approach two types of knowledge are combined: general knowledge about geolocations and pointsof interest and specialized knowledge about a particular domain, i.e. cultural heritage. We use a number of Linked Open Data sources and a number of general sources from the cultural heritage domain (including Art and Architecture Thesaurus, Union List of Artist Names) as well as data from several Dutch cultural institutions. We show three concrete scenarios where a tourist accesses localized information on hisiPhone about the current environment, events, artworks or persons, whichare enriched by Linked Open Data sources. We show that Linked Open Data sources in isolation are currently too limited to provide interesting semantic information but combined with each other and with a number of other sources a really informative location-based service can be created. 1
Comparing Vessel Trajectories using Geographical Domain Knowledge and Alignments
"... Abstract—This paper presents a similarity measure that combines low-level trajectory information with geographical domain knowledge to compare vessel trajectories. The similarity measure is largely based on alignment techniques. In a clustering experiment we show how the measure can be used to disco ..."
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Abstract—This paper presents a similarity measure that combines low-level trajectory information with geographical domain knowledge to compare vessel trajectories. The similarity measure is largely based on alignment techniques. In a clustering experiment we show how the measure can be used to discover behavior concepts in vessel trajectory data that are dependent both on the low-level trajectories and the domain knowledge. We also apply this measure in a classification task to predict the type of vessel. In this task the combined measure performs better than similarities based on domain knowledge or low-level information alone. Index Terms—vessel trajectories; trajectory alignments; geographical domain knowledge; trajectory clustering I.
Linked Open Piracy
"... There is an abundance of semi-structured reports on events being written and made available on the World Wide Web on a daily basis. These reports are primarily meant for human use. A recent movement is the addition of RDF metadata to make automatic processing by computers easier. A fine example of t ..."
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There is an abundance of semi-structured reports on events being written and made available on the World Wide Web on a daily basis. These reports are primarily meant for human use. A recent movement is the addition of RDF metadata to make automatic processing by computers easier. A fine example of this movement is the Open Government Data initiative which, by adding RDF metadata to spreadsheets and textual reports, strives to speed up the creation of geographical mashups and visual analytics applications. In this paper we present a new Open Linked Data RDF dataset1 and a method for automatically adding such RDF metadata to semi-structured reports. We showcase our method on piracy attack reports issued on the web by the International Chamber of Commerce’s International Maritime Bureau (ICC-CCS IMB) 2 We create a Semantic Web representation with the Simple Event Model (SEM) from screen scrapes of the ICC-CCS website. We show how the event layer makes it possible to easily analyze and visualize the aggregated reports to answer domain questions. Our pipeline includes conversion of the reports to RDF, linking their parts to external resources from the Linked Open Data cloud and exposing them to the Web through a ClioPatria web server that hosts the RDF.

