8,729 research outputs found
AR2SPARQL: An Arabic Natural Language Interface for the Semantic Web
With the growing interest in supporting the Arabic language on the Semantic Web (SW), there is an emerging need to enable Arab users to query ontologies and RDF stores without being challenged with the formal logic of the SW. In the domain of English language, several efforts provided Natural Language (NL) interfaces to enable ordinary users to query ontologies using NL queries. However, none of these efforts were designed to support the Arabic language which has different morphological and semantic structures.
As a step towards supporting Arabic Question Answering (QA) on the SW, this work presents AR2SPARQL, a NL interface that takes questions expressed in Arabic and returns answers drawn from an ontology-based knowledge base. The core of AR2SPARQL is the approach we propose to translate Arabic questions into triples which are matched against RDF data to retrieve an answer. The system uses both linguistic and semantic features to resolve ambiguity when matching words to the ontology content. To overcome the limited support for Arabic Natural Language Processing (NLP), the system does not make intensive use of sophisticated linguistic methods. Instead, it relies more on the knowledge defined in the ontology and the grammar rules we define to capture the structures of Arabic questions and to construct an adequate RDF representations. AR2SPARQL has been tested with two different datasets and results have shown that it achieves a good retrieval performance in terms of precision and recall
Introduction to the special issue on cross-language algorithms and applications
With the increasingly global nature of our everyday interactions, the need for multilingual technologies to support efficient and efective information access and communication cannot be overemphasized. Computational modeling of language has been the focus of
Natural Language Processing, a subdiscipline of Artificial Intelligence. One of the current challenges for this discipline is to design methodologies and algorithms that are cross-language in order to create multilingual technologies rapidly. The goal of this JAIR special
issue on Cross-Language Algorithms and Applications (CLAA) is to present leading research in this area, with emphasis on developing unifying themes that could lead to the development of the science of multi- and cross-lingualism. In this introduction, we provide the reader with the motivation for this special issue and summarize the contributions of the papers that have been included. The selected papers cover a broad range of cross-lingual technologies including machine translation, domain and language adaptation for sentiment
analysis, cross-language lexical resources, dependency parsing, information retrieval and knowledge representation. We anticipate that this special issue will serve as an invaluable resource for researchers interested in topics of cross-lingual natural language processing.Postprint (published version
Using Arabic Numbers (Singular, Dual, and Plurals) Patterns To Enhance Question Answering System Results
In the field of information retrieval, it is very difficult to answer the question entered by the user, because the search engine retrieve a ranked documents that contain any key word or phrase inside the documents, this need another extra effort to search the answer inside the documents, and there may be no answer. The alternative of search engine is a question answering system, which it retrieves the exact answer of the question in the natural language if found. A question answering system accepts the question in the natural, then many processes were done to extract the exact answer. In general a question answering system is composed of three main components: question classification module, information retrieval module and answer extraction module. A question answering system is applied in holy Quran which written and cited in Arabic language, some characteristic of the Arabic language were used to enhance the answer extraction, one of these important characteristics is numbering, singular, dual and plural. A prototype build uses special pattern used to process the number in Arabic language, which enhance the answers by adding more words and meaning. A corpus of questions and its answers from holy Quran used to test and answers the question
Using Linguistic Analysis to Translate Arabic Natural Language Queries to SPARQL
The logic-based machine-understandable framework of the Semantic Web often
challenges naive users when they try to query ontology-based knowledge bases.
Existing research efforts have approached this problem by introducing Natural
Language (NL) interfaces to ontologies. These NL interfaces have the ability to
construct SPARQL queries based on NL user queries. However, most efforts were
restricted to queries expressed in English, and they often benefited from the
advancement of English NLP tools. However, little research has been done to
support querying the Arabic content on the Semantic Web by using NL queries.
This paper presents a domain-independent approach to translate Arabic NL
queries to SPARQL by leveraging linguistic analysis. Based on a special
consideration on Noun Phrases (NPs), our approach uses a language parser to
extract NPs and the relations from Arabic parse trees and match them to the
underlying ontology. It then utilizes knowledge in the ontology to group NPs
into triple-based representations. A SPARQL query is finally generated by
extracting targets and modifiers, and interpreting them into SPARQL. The
interpretation of advanced semantic features including negation, conjunctive
and disjunctive modifiers is also supported. The approach was evaluated by
using two datasets consisting of OWL test data and queries, and the obtained
results have confirmed its feasibility to translate Arabic NL queries to
SPARQL.Comment: Journal Pape
Construction of an ontology for intelligent Arabic QA systems leveraging the Conceptual Graphs representation
The last decade had known a great interest in Arabic Natural Language Processing (NLP) applications. This interest is
due to the prominent importance of this 6th most wide-spread language in the world with more than 350 million native speakers.
Currently, some basic Arabic language challenges related to the high inflection and derivation, Part-of-Speech (PoS) tagging,
and diacritical ambiguity of Arabic text are practically tamed to a great extent. However, the development of high level and
intelligent applications such as Question Answering (QA) systems is still obstructed by the lacks in terms of ontologies and other
semantic resources. In this paper, we present the construction of a new Arabic ontology leveraging the contents of Arabic WordNet
(AWN) and Arabic VerbNet (AVN). This new resource presents the advantage to combine the high lexical coverage and semantic
relations between words existing in AWN together with the formal representation of syntactic and semantic frames corresponding
to verbs in AVN. The Conceptual Graphs representation was adopted in the framework of a multi-layer platform dedicated to
the development of intelligent and multi-agents systems. The built ontology is used to represent key concepts in questions and
documents for further semantic comparison. Experiments conducted in the context of the QA task show a promising coverage
with respect to the processed questions and passages. The obtained results also highlight an improvement in the performance of
Arabic QA regarding the c@1 measure.The work of the last author was carried out in the framework of the WIQ-EI IRSES project (Grant No. 269180) within the FP 7 Marie Curie, the DIANA APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project, and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Abouenour, L.; Nasri, M.; Bouzoubaa, K.; Kabbaj, A.; Rosso, P. (2014). Construction of an ontology for intelligent Arabic QA systems leveraging the Conceptual Graphs representation. Journal of Intelligent and Fuzzy Systems. 27(6):2869-2881. https://doi.org/10.3233/IFS-141248S2869288127
Arabic Quranic Search Tool Based on Ontology
This paper reviews and classifies most of the common types of search techniques that have been applied on the Holy Quran. Then, it addresses the limitations of these methods. Additionally, this paper surveys most existing Quranic ontologies and what are their deficiencies. Finally, it explains a new search tool called: a semantic search tool for Al-Quran based on Qur’anic on-tologies. This tool will overcome all limitations in the existing Quranic search applications
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