Query Translation Using Concepts Similarity Based on Quran Ontology for Cross-Language Information Retrieval

Abstract

In Cross-Language Information Retrieval (CLIR) process, the translation effects have a direct impact on the accuracy of follow-up retrieval results. In dictionary-based approach, we are dealing with the words that have more than one meaning which can decrease the retrieval performance if the query translation return an incorrect translations. These issues need to be overcome using efficient technique. In this study we proposed a Cross-Language Information Retrieval (CLIR) method based on domain ontology using Quran concepts for disambiguating translation of the query and to improve the dictionary-based query translation. For experimentation, we use Quran ontology written in English and Malay languages as a bilingual parallel-corpora and Quran concepts as a resource for cross-language query translation along with dictionary-based translation. For evaluation, we measure the performance of three IR systems. IR₁ is natural language query IR, IR₂ is natural language query CLIR based on dictionary (as a Baseline) and IR₃ is the retrieval of this research proposed method using Mean Average Precision (MAP) and average precision at 11 points of recall. The experimental result shows that our proposed method brings significant improvement in retrieval accuracy for English document collections, but deficient for Malay document collections. The proposed CLIR method can obtain query expansion effect and improve retrieval performance in certain language

Using Linguistic Analysis to Translate Arabic Natural Language Queries to SPARQL

“…This can be attributed to the lack of ontologies expressed in Arabic and the complexities associated with the NLP of Arabic text [3]. In general, there are four different categories of research concerning the Arabic language and the Semantic Web [11]: 1) the development of Arabic ontologies [12][13][14], 2) Using ontologies for improving Arabic named entities extraction [15,16], 3) Ontology based modelling of Islamic knowledge [17][18][19], and 4) supporting cross-language information retrieval [20,21]. In parallel with these efforts, little attention was paid to enable Arab users to query Arabic ontologies through NL interfaces.…”

“…This can be achieved by incorporating semantic similarity measures when comparing the query words with the ontology terms. To test the feasibility of our approach in practice, we will apply it to support question answering over popular ontologies that support Arabic, such as the Quranic Ontology [35], and other ontology-based Islamic resources [21,24]. Finally, we will explore approaches to enhance the parsing results by testing other parsers of Arabic text and comparing results.…”

Similarity algorithm for evaluating the coverage of domain ontology for semantic Web services

“…Research done by [25] hybrid several ontology evaluation approach including synonym types of similarity measures that focused on biomedical domain ontology. There are large numbers of domain ontology in Web, for example Hotel related ontology [26], service ontology [27] and Quran ontology [30]. Our study aims on the domain of Travel.…”

A Question Answering System on Holy Quran Translation Based on Question Expansion Technique and Neural Network Classification

“…This system has shown noteworthy results with respect to effectively retrieve the Quranic knowledge. At the same time, Yahya et al (2013) have presented a semantic search in the Holy Quran based on CrossLanguage Information Retrieval (CLIR). They produced a bilingual ontology for the Holy Quran made up of concepts based on Quranic Arabic corpus ontology that created by Dukes (2015) and they realized that the most of the documents are belonging to the main concept whereas others documents are not belonging to any of these concepts in English translation.…”