An Ontology Based Approach for Automatically Annotating Document Segments
This paper presents an approach for automatically annotating document segments within information rich texts using a domain ontology. The work exploits the logical structure of input documents in order to achieve its task. The underlying assumption behind this work is that segments in such documents embody self contained informative units. Another assumption is that segment headings coupled with a documents hierarchical structure offer informal representations of segment content; and that matching segment headings to concepts in an ontology/thesaurus can result in the creation of formal labels/meta-data for these segments. A series of experiments was carried out using the presented approach on a set of Arabic agricultural extension documents. The results of carrying out these experiments demonstrate that the proposed approach is capable of automatically annotating segments with concepts that describe a segments content with a high degree of accuracy.
Keywords: Annotation, text segments, ontology, metadata
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ABOUT THE AUTHORS
Maryam Hazman
She is a Researcher at Central Lab for Agricultural Experts Systems, Ministry of Agriculture and Land Reclamation. She received her Ph.D from Cairo University, Faculty of Computers and Information. Her research interests include: Text mining, Knowledge Engineering, Knowledge Discovery, and Information Management.
Samhaa R. El-Beltagy
She is an Associate Professor at Cairo University. She received her Ph.D. from the University of Southampton, UK. Her research interests include: Text mining, Agent and Multi-agent based systems and frameworks, Open and Adaptive hypermedia, and Distributed Information Management.
Ahmed Rafea
He received his Ph.D. from University Paul Sabatier, Toulouse, France and is currently a Computer Science Professor at the American University in Cairo. He is also the Scientific Adviser of the Central Lab. For Agricultural Expert System within the Egyptian Agriculture Research Center. Prof. Rafea authored over 130 scientific papers in International and National Journals and Conference Proceedings. His research interests include Natural Language Processing, Machine Translation, Knowledge Engineering, Knowledge Discovery, and Data Mining
Maryam Hazman
She is a Researcher at Central Lab for Agricultural Experts Systems, Ministry of Agriculture and Land Reclamation. She received her Ph.D from Cairo University, Faculty of Computers and Information. Her research interests include: Text mining, Knowledge Engineering, Knowledge Discovery, and Information Management.
Samhaa R. El-Beltagy
She is an Associate Professor at Cairo University. She received her Ph.D. from the University of Southampton, UK. Her research interests include: Text mining, Agent and Multi-agent based systems and frameworks, Open and Adaptive hypermedia, and Distributed Information Management.
Ahmed Rafea
He received his Ph.D. from University Paul Sabatier, Toulouse, France and is currently a Computer Science Professor at the American University in Cairo. He is also the Scientific Adviser of the Central Lab. For Agricultural Expert System within the Egyptian Agriculture Research Center. Prof. Rafea authored over 130 scientific papers in International and National Journals and Conference Proceedings. His research interests include Natural Language Processing, Machine Translation, Knowledge Engineering, Knowledge Discovery, and Data Mining
