Titlebook: Linguistic Linked Open Data; 12th EUROLAN 2015 Su Diana Trandab??,Daniela G?fu Conference proceedings 2016 Springer International Publishin

考得

Communications in Computer and Information Sciencehttp://image.papertrans.cn/l/image/586688.jpg

colony

棲息地

Conference proceedings 2016edia and the Web of Linked Data,?RUMOUR 2015, held in Sibiu, Romania, in July 2015...The 10 revised full papers presented together with 12 abstracts of tutorials werecarefully reviewed and selected from 21 submissions.?..?..?.

使人入神

Towards Social Data Analytics for Smart Tourism: A Network Science Perspective of a conceptual data model and of the development of a data processing workflow that allows to capture, to analyze and to query the implicit social network that was determined by the relations between user comments, using specialized software tools for graph databases and complex networks analytics.

AVANT

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Supplement

Towards Creating an Ontology of Social Media Textsvisualization of texts types is yet available. Going beyond the classification of texts in species and genres, this paper proposes an ontology which discusses the various text types, focusing on social media texts, and offering a set of properties to describe them.

endoscopy

Extracting Features from Social Media Networks Using Semanticsia exploration. Thus, it describes a tool useful for communication experts to analyse public speeches. So far, this tool gave promising results in inferring socio-political trends from social media content of public speakers. We also evaluated our experiment on Support Vector Machine (SVM) with 10-fold cross-validations.

放縱

1865-0929 n?Social Media and the Web of Linked Data,?RUMOUR 2015, held in Sibiu, Romania, in July 2015...The 10 revised full papers presented together with 12 abstracts of tutorials werecarefully reviewed and selected from 21 submissions.?..?..?.978-3-319-32941-3978-3-319-32942-0Series ISSN 1865-0929 Series E

大方一點(diǎn)

Ontological Modelling of Rumorso the temporal information associated with any statement. As we are dealing in first line with social media, our modelling work should also cover information diffusion networks and user online behavior, which can also help in classifying a statement as a rumor or a fact. We focus in this paper on the core of our rumor ontology.