We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of informat...
Abstract. The use of spreadsheets to capture information is widespread in industry. Spreadsheets can thus be a wealthy source of domain information. We propose to automatically ext...
Felienne Hermans, Martin Pinzger, Arie van Deursen
The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement ...
Mikalai Krapivin, Maurizio Marchese, Andrei Yadran...
This paper presents our work on the detection of temporal information in web pages. The pages examined within the scope of this study were taken from the tourism sector and the te...
In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple ent...
Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang...