Design of interactive intelligent assistant translation platform based on multi-strategies

Yan-hong, Dai

doi:10.1007/s10586-018-2310-0

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…In this way, users can be engaged in the corresponding interaction design and contribute the corresponding design concept to the corresponding value experience. As a kind of qualitative evaluation and analysis, it is mainly about implementing user's experience analysis based on the constructive method [30,31]. In this paper, the effective evaluation based on the corresponding community tolerance method is implemented through the combination of different circles.…”

Section: User's Experience Evaluationmentioning

confidence: 99%

Scientific Computing Evaluation of Interactive Product Art Design under the Background of User Experience Evaluation Analysis Model

Peng

Qin

2022

Mobile Information Systems

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Art comes from life, and art products derived from it are also closely related to daily life. With the development and improvement of social economy, art products are more and more favored and recognized by people. In other words, there will be higher requirements for the design of art products, including whether the design can bring people a visual feast, meet people's spiritual needs, and have practical functions or not. Based on these needs and deficiencies, this paper proposes a scientific computing evaluation of interactive product art design based on the user’s experience evaluation analysis model, combining the corresponding design strategies with interactive algorithms. In addition, by integrating the design business logic and simulation experiments of interactive art products, this paper discusses its fuzzy structure from the perspective of interaction, and analyzes fuzzy cognition and decision-making clustering strategies. The purpose of this is to support decision analysis and realize the effectiveness of user’s fuzzy cognitive strategies. The simulation experiment results show that users can directly observe the results according to the categories after applying the user’s experience evaluation analysis model, which greatly improves the efficiency and quality of product design. These findings clearly verify that the user’s experience evaluation analysis model proposed in this paper has a significant impact on interactive product art design and also provide convenience for scientific computing evaluation.

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Section: User's Experience Evaluationmentioning

confidence: 99%

Scientific Computing Evaluation of Interactive Product Art Design under the Background of User Experience Evaluation Analysis Model

Peng

Qin

2022

Mobile Information Systems

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“…The comparison results observed for the proposed methodology when compared to the AI‐Powered writing assistant, 11 STCAE, 12 SVM, 26 IATP, 14 Two‐stage hybrid classifier, 24 PBDA, 13 ANN, 28 and two‐stage hybrid classifier are presented in Table 10. The experiments are conducted in the testing dataset.…”

Section: Experimental Analysis and Resultsmentioning

confidence: 99%

“…Dai et al 14 provided an overall design of the Interactive Auxiliary Translation Platform (IATP) based on a multi‐strategy. In the English–Chinese translation system, they are computing the similarity between the sentences based on the syntactic and semantic meaning.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid support vector machine and K‐nearest neighbor‐based software testing for educational assistant

Ramesh

Radhika

Jothi

2022

Concurrency and Computation

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In terms of training students for work in diverse firms, traditional and out-of-date teaching techniques cannot compete with digital teaching methods. To overcome this problem, the teaching approach and content must be changed. An Educational Assistant for Software Testing (EAST) framework is developed in this work to train students to improve their skills in software testing via Computer Assisted Instruction (CAI) built using Natural Language Processing (NLP), Machine learning, and information retrieval techniques. In this paper, a Group Search Optimized two-stage hybrid Support Vector Machine-K-Nearest Neighbor (SVM-KNN) classifier is used to develop a novel approach for analyzing the parameters that introduce bugs in bug reports. To decrease the data sparsity problem, the group search optimization (GSO) algorithm is used to improve the parameter selection process of the two-stage hybrid classifier by generating optimal values for parameters such as k, c, and gamma. Two bug report datasets were used to test the model. The database for our application is built by collecting bug reports from a wide open-source community as well as several mobile application development companies. Based on the extensive experiments conducted via different performance metrics, we can conclude that the EAST framework can improve outdated teaching methodologies.

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“…Dai combines the latent semantic analysis of deep semantic structure, focuses on shallow text expressions, makes linear regression with the help of singular value decomposition technology in LSA, and discusses the coincidence rate of various text features on English composition performance prediction [19]. Chen et al selected some scoring items with a high linear fitting rate with the composition scores, trained the scoring engine, and calculated the distance between students' compositions and the standard corpus [20].…”

Section: Research On Intelligent Translation Algorithmmentioning

confidence: 99%

An Assisted Teaching Method of College English Translation Using Generative Adversarial Network

Zhang

2022

Mobile Information Systems

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College English translation instruction is an important part of developing students’ English application skills. The generation network in GAN (generative adversarial network) is combined with reinforcement learning technology in this paper to create a basic text generation model that solves the problem that the original GAN model cannot handle discrete data. The correctness of students’ English translation ability is analyzed using a neural network model trained by PSO (particle swarm optimization), which can help teachers estimate students’ translation ability and provide a reference for the next teaching. The results show that the proposed model’s accuracy rate is clearly higher than the comparison model’s, with a maximum accuracy rate of over 85%. The findings indicate that this research model has the potential to improve the quality of English translation instruction.

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Design of interactive intelligent assistant translation platform based on multi-strategies

Cited by 5 publications

References 7 publications

Scientific Computing Evaluation of Interactive Product Art Design under the Background of User Experience Evaluation Analysis Model

Scientific Computing Evaluation of Interactive Product Art Design under the Background of User Experience Evaluation Analysis Model

Hybrid support vector machine and K‐nearest neighbor‐based software testing for educational assistant

An Assisted Teaching Method of College English Translation Using Generative Adversarial Network

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