Visual analysis of documents with semantic graphs

In this paper, we present a technique for visual analysis of documents based on the semantic representation of text in the form of a directed graph, referred to as semantic graph. This approach can aid data mining tasks, such as exploratory data analysis, data description and summarization. In order to derive the semantic graph, we take advantage of natural language processing, and carry out a series of operations comprising a pipeline, as follows. Firstly, named entities are identified and coreference resolution is performed; moreover, pronominal anaphors are resolved for a subset of pronouns. Secondly, subject – predicate – object triplets are automatically extracted from the Penn Treebank parse tree obtained for each sentence in the document. The triplets are further enhanced by linking them to their corresponding co-referenced named entity, as well as attaching the associated WordNet synset, where available. Thus we obtain a semantic directed graph composed of connected triple...

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Delia Rusu, Blaz Fortuna, Dunja Mladenic, Marko Grobelnik, Ruben Sipos
• Keywords: Data Mining, KDD 2009, Natural Language Processing, Semantic Graph, Semantic Representation