Natural Language Processing and Big Data - An Ontology-Based Approach for Cross-Lingual Information Retrieval

Monti, Johanna; Monteleone, Mario; Buono, Maria Pia di; Marano, Federica

doi:10.1109/socialcom.2013.108

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…Monti et al [14] proposed a methodology for ontologybased CLIR. Italian-English retrieval has been evaluated using this approach for archaeological domain.…”

Section: Ontology-based Clirmentioning

confidence: 99%

“…CLIR systems [6][7][8][9][10] facilitate non-English users to pose natural language queries in their own languages but fail to handle semantics. A few research works [11][12][13][14][15] have been reported on ontology-based CLIR systems that deal with semantics using bilingual ontologies. However, very few approaches are evolved to build multilingual ontologies [16][17][18] automatically from available resources like text documents, databases, etc.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-based Tamil–English cross-lingual information retrieval system

Thenmozhi¹,

Aravindan²

2018

Sādhanā

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Cross-lingual information retrieval (CLIR) systems facilitate users to query for information in one language and retrieve relevant documents in another language. In general, CLIR systems translate query in source language to target language and retrieve documents in target language based on the keywords present in the translated query. However, the presence of ambiguity in source and translated queries reduces the performance of the system. Ontology can be used to address this problem. The current approaches to ontology-based CLIR systems use manually constructed multilingual ontology, which is expensive. However, many methods exist to automatically construct ontology for any domain in English but not in other languages like Tamil. We propose a methodology for Tamil-English CLIR system by translating the Tamil query to English and retrieve pages in English to address these issues. Our approach uses a word sense disambiguation module to resolve the ambiguity in Tamil query. An automatically constructed ontology in English is used to address the ambiguity of English query. We have developed a morphological analyser for Tamil language, Tamil-English bilingual dictionary and named entity database to translate a Tamil query to English. The translated query is reformulated using ontology and the reformulated queries are given to a search engine to retrieve English documents from the Internet. We have evaluated our methodology for agriculture domain and the evaluation results show that our approach outperforms other approaches in terms of precision.

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“…Monti et al [14] proposed a methodology for ontologybased CLIR. Italian-English retrieval has been evaluated using this approach for archaeological domain.…”

Section: Ontology-based Clirmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ontology-based Tamil–English cross-lingual information retrieval system

Thenmozhi¹,

Aravindan²

2018

Sādhanā

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“…Johanna Monti et al [20], puts an effort on Cross Language Information retrieval application where any language query is translated to a common language say English, and retrieve the information from web. The methodology is based on the Lexicon Grammar which encompasses both syntax and lexicon.…”

Section: Comparative Analysismentioning

confidence: 99%

A Review on Information Retrieval – Natural Language Processing Approach

Vijayalakshmi¹,

Manasamithra²

2018

IJCA

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Information retrieval is very important area in any of the IT applications. Systematic data storage is essential in information retrieval. In conventional method, data is stored in a structured format and retrieved using SQL queries which requires technical knowledge. Most common data storing and retrieving mechanism in IT is the Relational Database Management Systems. Now there is a necessity to retrieve data from a very large database using natural language from any social media. A brief survey of various methods used to store and retrieve data using Natural Language Processing (NLP) is carried out in this paper.

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“…Chimalakonda and K. V. Nori [28] J. Monti et al [29] proposed an approach based on ontology for cross-lingual information retrieval. The methodology is based upon the Lexicon-grammar (LG).…”

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confidence: 99%

Techniques of Ontology and its Usage in Indian Languages - A Review

Kaur¹,

Sharma²

2015

IJCA

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Ontology is presently an emerging research topic in the field of artificial intelligence, semantic web, and natural language processing, software engineering, and information architecture etc. Manual Ontology building is essentially a time consuming and tedious task. From the last few decades, different ontology building approaches are being used to build ontology either semi-automatically or automatically. This paper review has been carried out/done on the usage of different ontology building approaches in natural language processing and their usage on Indian languages. It is hereby concluded from the review that in Indian languages usage of ontology is very less because of the challenges to build ontology for minority languages.

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Natural Language Processing and Big Data - An Ontology-Based Approach for Cross-Lingual Information Retrieval

Cited by 6 publications

References 16 publications

Ontology-based Tamil–English cross-lingual information retrieval system

Ontology-based Tamil–English cross-lingual information retrieval system

A Review on Information Retrieval – Natural Language Processing Approach

Techniques of Ontology and its Usage in Indian Languages - A Review

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