Study on the Tibetan Information Retrieval Model based on LaBSE
With the growth of Tibetan resources and usage demand,it has become an important challenge to re-trieve the information required by users accurately.To solve the problem of query information and semantic matching between documents in Tibetan retrieval,a Tibetan information retrieval model based on LaBSE is pro-posed in this paper.For constructing the model,a LaBSE model was first used to extract feature information from Tibetan documents and then input the query information and feature information into the model together.Through pre-training tasks such as the mask language model and translation language model,the model learned the deep semantic information of different Tibetan characters from different contexts.Finally,fine-tuning was carried out to complete the construction of the model.The experimental results show that the accuracy of the Ti-betan information retrieval model constructed in this paper reaches 93.57％,which is 6.37％higher than that of the Tibetan information retrieval model based on BERT,indicating that our model can more effectively match the query information and Tibetan documents,which provides a reference for accurate retrieval of Tibetan resources.
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