Titlebook: Semantic Mashups; Intelligent Reuse of Brigitte Endres-Niggemeyer Book 2013 Springer-Verlag Berlin Heidelberg 2013 AI Mashup Challenge.DBpe

脫離

DBpedia Mashups,to find the machine representation of that knowledge. DBpedia constitutes a major part of the semantic data on the web. Its sheer size and wide coverage enables you to use it in many kind of mashups: it contains biographical, geographical, bibliographical data; as well as discographies, movie metada

Impugn

Mashups for the Web of Things,nnected objects, ranging from cars and transportation cargos to electrical appliances. In this chapter we provide a brief architectural overview of technologies which can be used in WoT mashups with emphasis on artificial intelligence technologies such as conceptualization and stream processing. We

FLEET

Mashups Using Mathematical Knowledge,ups and focuses on those that process mathematical . rather than, e.g., huge amounts of numeric ., as it is the structure of knowledge that distinguishes mathematics from other application domains..The resources that mathematical mashups process primarily include . and the services they offer involv

RENAL

Ingrained

拖債

Similarity Mashups for Recommendation,e Semantic Web and mashups can improve recommendation systems and provide new ways for their creation. In the web it is possible to analyze product descriptions and to use Linked Data for characterizing the similarity of objects or of objects and user interests. In this chapter, we give a brief over

Heterodoxy

Urban Mashups,ople moving in the city or extending it) and natural ones (rain or climate changes). Cities are potentially huge sources of data of any kind and for the last years a lot of effort has been put in order to create and extract those sources. This scenario offers a lot of opportunities for mashup develo

ethnology

Travel Mashups,d as a side effect of their use, generate content that feeds back into optimization of these services. The resulting (integrated) platforms support users in and across different facets of life, including discovery and exploration, travel and tourism. This chapter discusses the creation and use of .,

Subdue

Analogy

Similarity Mashups for Recommendation,scriptions and to use Linked Data for characterizing the similarity of objects or of objects and user interests. In this chapter, we give a brief overview of existing technical approaches and tools for creating recommendation systems that can be used to create mashups as recommendation systems.