Titlebook: Knowledge Engineering and Semantic Web; 8th International Co Przemys?aw Ró?ewski,Christoph Lange Conference proceedings 2017 Springer Inter

ADAGE

Obverse

Russian Tagging and Dependency Parsing Models for Stanford CoreNLP Natural Language Toolkit an extensible pipeline that provides core natural language analysis. Russian belongs to morphologically rich languages and demands full morphological analysis including annotating input texts with POS tags, features and lemmas (unlike the case of case-, person-, etc. insensitive languages when stem

JOT

expdient

嫻熟

QSMat: Query-Based Materialization for Efficient RDF Stream Processingither the maintenance of a stream window materialization or the evaluation of a query over the stream. . exploits knowledge of a given query and entailment rule-set to accelerate window materialization by avoiding inferences that provably do not affect the evaluation of the query. We prove that stre

cajole

Employing Link Differentiation in Linked Data Semantic Distanceh structure of LOD is utilized to measure inter-resource relatedness via their semantic distance in the graph. The intuition behind this approach is that the more connected resources are to each other, the more related they are. The drawback of this approach is that it treats all inter-resource conn

outskirts

Ontology for Representing Human Needseconomic policy. This notwithstanding, the concept of need has not yet found its place in information systems and online tools. Furthermore, assessing needs itself remains a labor-intensive, mostly offline activity, where only a limited support by computational tools is available. In this paper, we

行乞

Knowledge Graph: Semantic Representation and Assessment of Innovation Ecosystemstage. Hence, being able to identify, locate, measure, and assess competence occupants can be a decisive competitive edge. In this work, we introduce a framework that assists with performing such tasks. To achieve this, NLP-, rule-based, and machine learning techniques are employed to process raw dat

Mingle

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