English-Hindi Cross Language Information Retrieval System: Query Perspective

Bajpai, Pratibha; Verma, Parul; Abbas, S. Qasim

doi:10.3844/jcssp.2018.705.713

Cited by 2 publications

(1 citation statement)

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“…Bajpai et al, discussed the development process of a complete English to Hindi cross-language information retrieval system and the contribution of each component to the system. The experimental results obtained by him confirm that adding the component "analyzer" to the CLIR architecture improves the efficiency of disambiguation algorithm (Bajpai et al, 2018). The electronic dictionary system has become very important in today's society.…”

Section: Related Workmentioning

confidence: 74%

Construction of artificial intelligence-assisted English learning resource query system

Yao

2022

Front. Psychol.

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English has become an important tool for China's opening to the outside world and exchanges with other countries. More and more people have the motivation and requirements to learn English, but under the traditional English learning mode and traditional teaching mode, the cultivation of learners' autonomous learning habits is ignored. This article aims to study the construction of artificial intelligence-assisted English learning resource query system and establish the relevant feedback mechanism of retrieval. This article applies this mechanism to the retrieval of learning resources, so as to provide learners with the learning resources they really need and improve learners' learning efficiency. This article proposes to find the relevant knowledge points by extracting the knowledge points of the retrieval content. It realizes the query expansion based on knowledge and then realizes the expansion of retrieval results. It realizes the mapping of knowledge points on the retrieval content, the query and expansion of knowledge points, and the presentation of learning resources of the knowledge point index. It also uses the relevant feedback mechanism to adjust the retrieval results to meet the retrieval needs of learners. The experimental results show that the number of knowledge points can be increased to 2–4 times by query expansion based on English resources. Thus, the number of learning resources of search results can be increased to 3–10 times, the expansion of search results can be realized, and the overall recall will be greatly improved. In this article, the related methods of artificial intelligence are applied to the construction experiment of the English learning resource query system, which has a certain promotion effect on the construction of the system.

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Section: Related Workmentioning

confidence: 74%