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New approach for topic segmentation of railway text Boudouma Rachid, Touahni Raja, Messoussi Rochdi LASTID, Univ of IBN TOFAIL, Kenitra, Morocco Online published on 20 June, 2013. Abstract We suggest in this paper a new approach for topic segmentation of railway textual documents which is based both on domain ontology and neural networks (Hopfield's networks) with Topic Quantity of Information as value of the spin magnitude in the network. Our approach incorporates also a discursive analysis of the text to further improve the results. We present also our automatic system SeThemO (Thematic Segmentation-based Ontology) which implements this approach. Finally, we evaluate its effectiveness by using a text corpus formed by concatenated sections dealing with different railway topics. Top Keywords Domain Ontology, railway, neural networks, Hopfield networks, topic borders, topic segmentation, discursive analysis. Top | |
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