Text mining using nonnegative matrix factorization and latent semantic analysis

Hassani, Ali; Iranmanesh, Amir; Mansouri, N.

doi:10.1007/s00521-021-06014-6

Cited by 32 publications

(14 citation statements)

References 32 publications

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“…However, several issues and challenges are brought up when it comes to using text mining. The most widely discussed are context specificities associated with the user and problem being dealt with, language barriers, and human communication issues, such as sarcasm and irony [76].…”

Section: Text Mining and Semantic Network Analysismentioning

confidence: 99%

An Exploratory Study of Electronic Word-of-Mouth Focused on Casino Hotels in Las Vegas and Macao

Tang

Kim

2022

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In order to investigate the key attributes of casino hotel customer eWOM and their structural relationships, this study selects two casino hotels located in Las Vegas and Macao. Through big data analytics, online reviews of two casino hotels from Google Travel were utilized. The frequency and CONCOR analyses showed the top 50 high-frequency words for each hotel and divided them into groups. The results of the factor analysis and linear regression analysis show that four factors, namely “Physical Environment”, “Entertainment”, “Experience”, and “Amenity”, in Las Vegas have a significant impact on customer satisfaction, while two factors, namely “Value” and “Physical Environment”, do in Macao. Through the results, the study points out the general characteristics affecting customer satisfaction of casino hotels, as well as the distinctions in influencing factors of their customer satisfaction in different source markets.

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Section: Text Mining and Semantic Network Analysismentioning

confidence: 99%

An Exploratory Study of Electronic Word-of-Mouth Focused on Casino Hotels in Las Vegas and Macao

Tang

Kim

2022

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“…Latent semantic analysis (LSA) is a widely used method in the field of natural language processing [10]. It assumes that if two words appear more than once in the same document, then the two words are semantically similar.…”

Section: Lsa Modelmentioning

confidence: 99%

Design of language assisted learning model and online learning system under the background of artificial intelligence

Jin-xiang

2022

Applied Mathematics and Nonlinear Sciences

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This paper aiming at the problems of scattered operation types, poor extraction effect of learning resources and incomplete assignment of learning tasks in the online language learning platform designs a language assisted learning model under the background of artificial intelligence, proposes an English learning resource extraction algorithm based on the integration of LSA and N-gram models and then proposes a weighted multi-task learning model and it is optimized to improve the sparsity of learning variables. Finally, based on the construction of the assisted learning model, the online language learning system is designed, including demand analysis, overall design and architecture design, to improve the pertinence and efficiency of English learning.

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“…In the cloud environment, in order to divide the data well, cluster analysis can set up different groups, group similar data into one group, and group unrelated data or data with small correlation into one group [24]. erefore, the introduction of the concept of "distance" can know the correlation between the data, that is, the similarity of the data, and at the same time, it can increase the efficiency of sample classification.…”

Section: Cluster Analysismentioning

confidence: 99%

Big Data Clustering Mining Based on Swarm Intelligence Algorithm in Cloud Environment

Yan

2022

Mobile Information Systems

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As science and technology progress and develop rapidly in this day and age, various industry applications have changed the data in a new way, and the explosive growth of data has made traditional data mining unable to perform the current data mining work. The aim of this paper is to study the aggregation digging of big data based around flocking automation algorithms under circumstances of cloud. There is a fuzzy-mean aggregation arrangement with mixed frog leaping in this paper. Through simulation analysis of different clustering algorithms, hybrid frog-hopping and as well as the merging arrangement introduced in this paper, it is concluded that the merging algorithm achieves an improvement of up to 90% accuracy on the iritual membrane dataset. It was demonstrated that the arrangement provides effective agglomerations. When the number of iterations is 500, the fitness value of the algorithm on Dataset 1 is 1.59 × 104, and its convergence speed is faster than the other algorithms.

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Text mining using nonnegative matrix factorization and latent semantic analysis

Cited by 32 publications

References 32 publications

An Exploratory Study of Electronic Word-of-Mouth Focused on Casino Hotels in Las Vegas and Macao

An Exploratory Study of Electronic Word-of-Mouth Focused on Casino Hotels in Las Vegas and Macao

Design of language assisted learning model and online learning system under the background of artificial intelligence

Big Data Clustering Mining Based on Swarm Intelligence Algorithm in Cloud Environment

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