A Hybrid Approach for Arabic Semantic Relation Extraction

Information retrieval applications are essential tools to manage the huge amount of information in the Web. Ontologies have great importance in these applications. The idea here is that several data belonging to a domain of interest are represented and related semantically in the ontology, which can help to navigate, manage and reuse these data. Despite of the growing need of ontology, only few works were interested in Arabic language. Indeed, arabic texts are highly ambiguous, especially when diacritics are absent. Besides, existent works does not cover all the types of se-mantic relations, which are useful to structure Arabic ontol-ogies. A lot of work has been done on cooccurrence- based techniques, which lead to over-generation. In this paper, we propose a new approach for Arabic se-mantic relation extraction. We use vocalized texts to reduce ambiguities and propose a new distributional approach for similarity calculus, which is compared to cooccurrence. We discuss our contribution through experimental results and propose some perspectives for future research.