This paper presents a supervised machine learning approach for summarizing legal documents. A commercial system for the analysis and summarization of legal documents provided us wi...
An overwhelming number of legal documents is available in digital form. However, most of the texts are usually only provided in a semi-structured form, i.e. the documents are stru...
Named entities play an important role in Information Extraction. They represent unitary namable information within text. In this work, we focus on groups of named entities of the s...
A bitext, or bilingual parallel corpus, consists of two texts, each one in a different language, that are mutual translations. Bitexts are very useful in linguistic engineering bec...
Implicit information embedded in semantic web graphs, such as topography, clusters, and disconnected subgraphs is difficult to extract from text files. Visualizations of the graph...