Usage of singular value decomposition matrix for search latent semantic structures in natural language texts

Kuandykov, A.A.; Daineko, Yevgeniya; Baiburin, Yerzhan; Nugumanova, Aliya

doi:10.1109/sice.2015.7285567

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…The maximum number of topics generated was equal to the number of documents in the corpus. For extracting a few topics (k), the topmost k singular values were taken from the matrix ΣΣt [17, 33]. The procedure to be adopted for rank lowering and SVD is explained with in following example:Text is represented as a matrix of form X = U∑V t such that each row stands for unique word and each column represents unique document.…”

Section: Methodsmentioning

confidence: 99%

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Singh

Modi

2019

Heliyon

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Eye gaze tracking has been used to study the influence of visual stimuli on consumer behavior and attentional processes. Eye gaze tracking techniques have made substantial contributions in advertisement design, human computer interaction, virtual reality and disease diagnosis. Eye gaze estimation is considered critical for prediction of human attention, and hence indispensable for better understanding human activities. In this paper, Latent Semantic Analysis is used to develop an information model for identifying emerging research trends within eye gaze estimation techniques. An exhaustive collection of 423 titles and abstracts of research papers published during 2005–2018 were used. Five major research areas and ten research trends were classified based upon this study.

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Section: Methodsmentioning

confidence: 99%

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Singh

Modi

2019

Heliyon

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“…The maximum number of topics generated was equal to the number of documents in the corpus. For extracting a few topics (k), the topmost k singular values were taken from the matrix P P t [27,28]. Text is represented as a matrix of form X = U∑V t such that each row stands for unique word and each column represents unique document.…”

Section: U: Initial Rotation ∑: Scalingmentioning

confidence: 99%

Understanding Research Trends in Android Malware Research Using Information Modelling Techniques

Singh¹,

Gera²,

Ali³

et al. 2021

Computers, Materials &Amp; Continua

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Android has been dominating the smartphone market for more than a decade and has managed to capture 87.8% of the market share. Such popularity of Android has drawn the attention of cybercriminals and malware developers. The malicious applications can steal sensitive information like contacts, read personal messages, record calls, send messages to premium-rate numbers, cause financial loss, gain access to the gallery and can access the user's geographic location. Numerous surveys on Android security have primarily focused on types of malware attack, their propagation, and techniques to mitigate them. To the best of our knowledge, Android malware literature has never been explored using information modelling techniques. Further, promulgation of contemporary research trends in Android malware research has never been done from semantic point of view. This paper intends to identify intellectual core from Android malware literature using Latent Semantic Analysis (LSA). An extensive corpus of 843 articles on Android malware and security, published during 2009-2019, were processed using LSA. Subsequently, the truncated singular Value Decomposition (SVD) technique was used for dimensionality reduction. Later, machine learning methods were deployed to effectively segregate prominent topic solutions with minimal bias. Apropos to observed term and document loading matrix values, this five core research areas and twenty research trends were identified. Further, potential future research directions have been detailed to offer a quick reference for information scientists. The study concludes to the fact that Android security is crucial for pervasive Android devices. Static analysis is the most widely investigated core area within Android security research and is expected to remain in trend in near future. Research trends indicate the need for a faster yet effective model to detect Android applications causing obfuscation, financial attacks and stealing user information.

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Section: Singular Vector Decompositionmentioning

confidence: 99%

Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap

Sehra

Singh

2017

IJGI

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OpenStreetMap (OSM), based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA) to help identify the emerging research trends in OSM. An extensive corpus of 485 academic abstracts of papers published during the period 2007-2016 was used. Five core research areas and fifty research trends were identified in this study. In addition, potential future research directions have been provided to aid geospatial information scientists, technologists and researchers in undertaking future OSM research.

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Usage of singular value decomposition matrix for search latent semantic structures in natural language texts

Cited by 6 publications

References 7 publications

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review

Understanding Research Trends in Android Malware Research Using Information Modelling Techniques

Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap

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