Ontology-Based Question Analysis Method

Besbes, Ghada; Baazaoui-Zghal, Hajer; Moreno, António

doi:10.1007/978-3-642-40769-7_9

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Moreover, ontologies characterize and describe domain knowledge clearly in an auto-readable structure, and thus can be incorporated into machine-based formations designed to accelerate assessment, aid the reflexive annotation of net resources, and perform logical work [44]. Reference [45] suggested a novel question analysis process that employed ontologies, signifying a standard structure of queries by applying type-recognized graphs, and combining domain the ontologies and a lexicon-syntactic structure for query reformulation.…”

Section: Ontologymentioning

confidence: 99%

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Arbaaeen

Shah

2021

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For many users of natural language processing (NLP), it can be challenging to obtain concise, accurate and precise answers to a question. Systems such as question answering (QA) enable users to ask questions and receive feedback in the form of quick answers to questions posed in natural language, rather than in the form of lists of documents delivered by search engines. This task is challenging and involves complex semantic annotation and knowledge representation. This study reviews the literature detailing ontology-based methods that semantically enhance QA for a closed domain, by presenting a literature review of the relevant studies published between 2000 and 2020. The review reports that 83 of the 124 papers considered acknowledge the QA approach, and recommend its development and evaluation using different methods. These methods are evaluated according to accuracy, precision, and recall. An ontological approach to semantically enhancing QA is found to be adopted in a limited way, as many of the studies reviewed concentrated instead on NLP and information retrieval (IR) processing. While the majority of the studies reviewed focus on open domains, this study investigates the closed domain.

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Section: Ontologymentioning

confidence: 99%

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Arbaaeen

Shah

2021

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“…This method has been adopted by many researchers, Alawajy [7] used domain ontologies and the Arabic WordNet (AWN) to provide reliable extended keywords in order to enhance Arabic web content retrieval. Besbes [8] proposed a new question analysis method based on ontologies, it consists of representing generic structures of questions by using typed attributed graphs and integrating domain ontologies and lexico-syntactic patterns for query reformulation.…”

Section: Related Workmentioning

confidence: 99%

A Portable Natural Language Interface to Arabic Ontologies

Hakkoum¹,

Kharrazi²,

Raghay³

2018

ijacsa

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With the growing expansion of the semantic web and its applications, providing natural language interfaces (NLI) to end-users becomes essential to querying RDF stores and ontologies, using simple questions expressed in natural language. Existing NLIs work mostly with the English language. There are very few attempts to develop systems supporting the Arabic language. In this paper, we propose a portable NLI to Arabic ontologies; it will transform the user's query expressed in Arabic into formal language query. The proposed system starts by a preparation phase that creates a gazetteer from the given ontology. The issued query is then processed using natural language processing (NLP) techniques to extract keywords. These keywords are mapped to the ontology entities, then a valid SPARQL query is generated based on the ontology definition and the reasoning capabilities of the Web Ontology Language (OWL). To evaluate our tool we used two different Arabic ontologies: a Qur'anic ontology and an Arabic sample of Mooney Geography dataset. The proposed system achieved 64% recall and 76% precision.

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Analysing, Representing and Classifying Neuroscience Questions Using Ontologies

Eshghishargh

Gray

2021

Brain Informatics

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Ontology-Based Question Analysis Method

Cited by 4 publications

References 8 publications

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

A Portable Natural Language Interface to Arabic Ontologies

Analysing, Representing and Classifying Neuroscience Questions Using Ontologies

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