PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Document Visualization Based on Semantic Graphs
Delia Rusu, Blaz Fortuna, Dunja Mladenić, Marko Grobelnik and Ruben Sipoš
In: International Conference on Information Visualisation, 15-17 July 2009, Barcelona, Spain.


In this paper, we present a document visualization technique for data analysis based on the semantic representation of text in the form of a directed graph, referred to as semantic graph. It is derived using natural language processing as follows. Firstly subject– verb – object triplets are automatically extracted from the Penn Treebank parse tree obtained for each sentence in the document. Secondly, the triplets are further enhanced by linking them to their corresponding co-referenced named entity, by resolving pronominal anaphors as well as attaching the associated WordNet synset. Starting from the document's semantic graph and the list of extracted triplets we automatically generate the document summary, for which we also derive the semantic representation.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Information Retrieval & Textual Information Access
ID Code:6469
Deposited By:Jan Rupnik
Deposited On:08 March 2010