Visibility Analysis on the Web Using Co-visibilities and Semantic Networks

Author(s):  
Peter Kiefer ◽  
Klaus Stein ◽  
Christoph Schlieder
2015 ◽  
Vol 21 (5) ◽  
pp. 661-664
Author(s):  
ZORNITSA KOZAREVA ◽  
VIVI NASTASE ◽  
RADA MIHALCEA

Graph structures naturally model connections. In natural language processing (NLP) connections are ubiquitous, on anything between small and web scale. We find them between words – as grammatical, collocation or semantic relations – contributing to the overall meaning, and maintaining the cohesive structure of the text and the discourse unity. We find them between concepts in ontologies or other knowledge repositories – since the early ages of artificial intelligence, associative or semantic networks have been proposed and used as knowledge stores, because they naturally capture the language units and relations between them, and allow for a variety of inference and reasoning processes, simulating some of the functionalities of the human mind. We find them between complete texts or web pages, and between entities in a social network, where they model relations at the web scale. Beyond the more often encountered ‘regular’ graphs, hypergraphs have also appeared in our field to model relations between more than two units.


Author(s):  
N. Anastopoulou ◽  
M. Kavouras ◽  
M. Kokla ◽  
E. Tomai

Abstract. Research on knowledge discovery in the geospatial domain currently focuses on semi-structured, even on unstructured rather than fully structured content. The attention has been put on the plethora of resources on the Web, such as html pages, news articles, blogs, social media etc. Semantic information extraction in geospatial-oriented approaches is further used for semantic analysis, search, and retrieval. The aim of this paper is to extract, analyse and visualize geospatial semantic information and emotions from texts on climate change. A collection of articles on climate change is used to demonstrate the developed approach. These articles describe environmental and socio-economic dimensions of climate change across the Earth, and include a wealth of information related to environmental concepts and geographic locations affected by it. The results are analysed in order to understand which specific human emotions are associated with environmental concepts and/or locations, as well as which environmental terms are linked to locations. For the better understanding of the above-mentioned information, semantic networks are used as a powerful visualization tool of the links among concepts – locations – emotions.


2008 ◽  
Vol 11 (2) ◽  
pp. 83-85
Author(s):  
Howard Wilson
Keyword(s):  

2005 ◽  
Vol 8 (1) ◽  
pp. 16-18
Author(s):  
Howard F. Wilson
Keyword(s):  

1999 ◽  
Vol 3 (2) ◽  
pp. 6-6
Author(s):  
Barbara Shadden
Keyword(s):  

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