Similar Search Results

SenU-PTM: a novel phrase-based topic model for short-text topic discovery by exploiting word embeddings

Lu, Heng-Yang; Zhang, Yi; Du, Yuntao - In: Data Technologies and Applications 55 (2021) 5, pp. 643-660

Purpose Topic model has been widely applied to discover important information from a vast amount of unstructured data. Traditional long-text topic models such as Latent Dirichlet Allocation may suffer from the sparsity problem when dealing with short texts, which mostly come from the Web. These...

Persistent link: https://www.econbiz.de/10014712624

A data-driven neural network architecture for sentiment analysis

Çano, Erion; Morisio, Maurizio - In: Data Technologies and Applications 53 (2018) 1, pp. 2-19

Purpose The fabulous results of convolution neural networks in image-related tasks attracted attention of text mining, sentiment analysis and other text analysis researchers. It is, however, difficult to find enough data for feeding such networks, optimize their parameters, and make the right...

Persistent link: https://www.econbiz.de/10014712638

Identification of operational demand in law enforcement agencies : An application based on a probabilistic model of topics

Basilio, Marcio Pereira; Pereira, Valdecy; Brum, Gabrielle - In: Data Technologies and Applications 53 (2019) 3, pp. 333-372

Purpose The purpose of this paper is to develop a methodology for knowledge discovery in emergency response service databases based on police occurrence reports, generating information to help law enforcement agencies plan actions to investigate and combat criminal activities....

Persistent link: https://www.econbiz.de/10014712792

Topic optimization–incorporated collaborative recommendation for social tagging

Pan, Xuwei; Zeng, Xuemei; Ding, Ling - In: Data Technologies and Applications 58 (2022) 3, pp. 407-426

Purpose With the continuous increase of users, resources and tags, social tagging systems gradually present the characteristics of “big data” such as large number, fast growth, complexity and unreliable quality, which greatly increases the complexity of recommendation. The contradiction...

Persistent link: https://www.econbiz.de/10015342730

Techniques to detect terrorists/extremists on the dark web: a review

Alghamdi, Hanan; Selamat, Ali - In: Data Technologies and Applications 56 (2022) 4, pp. 461-482

extraction can be used as topic modeling with content analysis and text clustering. Originality/value At the end of the review …

Persistent link: https://www.econbiz.de/10014712711

Recognition and labeling of faults in wind turbines with a density-based clustering algorithm

Luo, Shuai; Liu, Hongwei; Qi, Ershi - In: Data Technologies and Applications 55 (2021) 5, pp. 841-868

-based clustering algorithm, named contour density scanning clustering (CDSC) algorithm. Design/methodology/approach The algorithm … algorithm in comparison with other conventional clustering algorithms, including k-means , density-based spatial clustering of … applications with noise, density peaking clustering, neighborhood grid clustering, support vector clustering, random forest, core …

Persistent link: https://www.econbiz.de/10014712752

A scalable eigenspace-based fuzzy c-means for topic detection

Murfi, Hendri - In: Data Technologies and Applications 55 (2021) 4, pp. 527-541

. Design/methodology/approach The eigenspace-based fuzzy c-means (EFCM) combines representation learning and clustering. The …

Persistent link: https://www.econbiz.de/10014712781

Practice challenge recommendations in online judge using implicit rating extraction and utility sequence patterns

P Natarajan, Ramesh; S, Kannimuthu; D, Bhanu - In: Data Technologies and Applications 58 (2024) 5, pp. 718-741

remove outliers, sequence-based learner clustering and utility sequence pattern mining approaches are used in the proposed … similarity-based learner clustering was used in transition matrix. Utilizing the rating as a utility in the USPAN algorithm …

Persistent link: https://www.econbiz.de/10015342729

Hybrid data analytic technique for grading fairness

Banditwattanawong, Thepparit; Jankasem, Arnon Marco Polo; … - In: Data Technologies and Applications 57 (2022) 1, pp. 18-31

Purpose Fair grading produces learning ability levels that are understandable and acceptable to both learners and instructors. Norm-referenced grading can be achieved by several means such as z score, K -means and a heuristic. However, these methods typically deliver the varied degrees of...

Persistent link: https://www.econbiz.de/10014712612