Research on high-performance English translation based on topic model

Shen, Yumin; Guo, Hongyu

doi:10.1016/j.dcan.2022.03.015

Cited by 4 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [182], it is reported that algorithms based on these principles present advantages over other existing algorithms for IR in the context of big data and for determining parameters in sets of data streams without ending. This procedure has been advantageously applied in automatic translation with a topic model obtained from the LSA and a subsequent adjustment with the PLSA [183]. However, these claims should be re-examined.…”

Section: Algorithm Initializationmentioning

confidence: 99%

Revisiting Probabilistic Latent Semantic Analysis: Extensions, Challenges and Insights

Figuera,

García Bringas

2024

Technologies

View full text Add to dashboard Cite

This manuscript provides a comprehensive exploration of Probabilistic latent semantic analysis (PLSA), highlighting its strengths, drawbacks, and challenges. The PLSA, originally a tool for information retrieval, provides a probabilistic sense for a table of co-occurrences as a mixture of multinomial distributions spanned over a latent class variable and adjusted with the expectation–maximization algorithm. The distributional assumptions and the iterative nature lead to a rigid model, dividing enthusiasts and detractors. Those drawbacks have led to several reformulations: the extension of the method to normal data distributions and a non-parametric formulation obtained with the help of Non-negative matrix factorization (NMF) techniques. Furthermore, the combination of theoretical studies and programming techniques alleviates the computational problem, thus making the potential of the method explicit: its relation with the Singular value decomposition (SVD), which means that PLSA can be used to satisfactorily support other techniques, such as the construction of Fisher kernels, the probabilistic interpretation of Principal component analysis (PCA), Transfer learning (TL), and the training of neural networks, among others. We also present open questions as a practical and theoretical research window.

show abstract

Section: Algorithm Initializationmentioning

confidence: 99%

Revisiting Probabilistic Latent Semantic Analysis: Extensions, Challenges and Insights

Figuera,

García Bringas

2024

Technologies

View full text Add to dashboard Cite

show abstract

“…This is important as not all translating machine can have a sense of feeling towards a certain topic. Only a few models have been developed that allegedly have good accretion capabilities in providing translation results such as Probabilistic Latent Semantic Analysis (PLSA) (Shen & Guo, 2022).…”

Section: Introductionmentioning

confidence: 99%

Post-Editing Machine Translation (PEMT) as the preference method for university students in Indonesia

Haiyudi,

Pratama,

Art-in

2023

ELTF

View full text Add to dashboard Cite

Language translating process by Indonesian students is particularly suffered from many errors. Its defined strategy should be carefully watched due to completing its translating perfection. Thus, this study identifies the problematic translation ways commonly referred and used by university students in Indonesia. The mixed method using embedded design between qualitative and quantitative data with a case study approach was carried out to find the preferences of the translation method used by the students. The respondents are 50 English Department students from different levels of studying years. The result shows that Post-Editing Machine Translation (PEMT) was preferred among other translating methods. The reasons are related to the ease and quality of the translation work. 76.90% of the students responded and chose to have PEMT as the preference. However, there were only 53.8% of them implementing PEMT as the translating process, and 38.5% were familiar with Machine Translation (MT) without post-editing instead. It indicates an inconsistency in the use of the translation methods as each of them experienced and chose different type of methods. However, PEMT was placed as the most referred translating method used by the students. This suggests that the presence of technology is well utilized while still paying attention to the quality of the translation through the post-editing process.

show abstract

BAS-ALSTM: analyzing the efficiency of artificial intelligence-based English translation system

Li,

Huang

2023

J Ambient Intell Human Comput

View full text Add to dashboard Cite

Research on high-performance English translation based on topic model

Cited by 4 publications

References 9 publications

Revisiting Probabilistic Latent Semantic Analysis: Extensions, Challenges and Insights

Revisiting Probabilistic Latent Semantic Analysis: Extensions, Challenges and Insights

Post-Editing Machine Translation (PEMT) as the preference method for university students in Indonesia

BAS-ALSTM: analyzing the efficiency of artificial intelligence-based English translation system

Contact Info

Product

Resources

About