Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Maximum Entropy Markov Models for Information Extraction and Segmentation
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Proceedings of the 6th International Conference on Semantic Systems
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This paper reports our research work carried out for developing intelligent information systems using citation context information extracted from research articles. We explain in this paper the steps followed for identifying, extracting and managing contextual data from articles published in ESWC series. Reporting on the amount of triplification data produced in the process, we describe our application developed for providing value added information services for the research community.