Jawad Makki

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Many authors can share the same name and this constitutes a serious problem that affects the relevancy of retrieval results and constitutes our motivation of finding such approach to cover this issue at the author names entity level. Solving such a problem may return with positive gain at the level of document retrieval, web search and the quality of data.(More)
One of the challenging tasks in the context of Ontological Engineering is to automatically or semi-automatically support the process of Ontology Learning and Ontology Population from semi-structured documents (texts). In this paper we describe a Semi-Automatic Ontology Instantiation method from natural language text, in the domain of Risk Management. This(More)
One of the challenging tasks in the context of Ontological Engineering is to automatically or semi-automatically support the process of Ontology Learning and Ontology Population from semi-structured documents (texts). In this paper we describe a Semi-Automatic Ontology Instantiation method from natural language text, in the domain of Risk Management. This(More)
In this paper we propose an NLP-based Ontology Population approach for a Generic Structure instantiation from natural language texts, in the domain of Risk Management. The approach is semi-automatic and based on combined NLP techniques using domain expert intervention for control and validation. It relies on the predicative power of verbs in the(More)
With the enormous growth of data, retrieving information from the Web became more desirable and even more challenging because of the Big Data issues (e.g. noise, corruption, bad quality...etc.). Expert seeking, defined as returning a ranked list of expert researchers given a topic, has been a real concern in the last 15 years. This kind of task comes in(More)
In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules(More)
Ontology Population supports the process of building ontologies in the complex task of instantiating ontology. Performing this process manually is both expensive and time consuming; this logically leads to attempts of fully or partially automating the process of acquisition and absorption of knowledge in general and the process of Ontology Population in(More)
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