Research on application of article recommendation algorithm based on Word2Vec and Tfidf

Wang, Rui; Shi, Yuliang

doi:10.1109/eebda53927.2022.9744824

Cited by 9 publications

(5 citation statements)

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“…The results of their experiments revealed that the CPAMF results were better than those of the cosine measure and BM25 by a healthy margin. For research article categorization, some authors have proposed hybrid approaches [19], [27], [28], [29], [30]. In these approaches, feature extraction is performed utilizing DL techniques and classification based on ML and DL methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms

et al. 2023

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Section: Literature Reviewmentioning

confidence: 99%

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms

et al. 2023

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“…Algorithms dealing with this task usually need to represent the input text as a vector with a fixed size [27]. The simplest method for creating word vectors from documents is TF (term frequency) [28], which is calculated according to (1):…”

Section: Term Frequency-inverse Document Frequencymentioning

confidence: 99%

Coreference Resolution for Improving Performance Measures of Classification Tasks

Šteflovič,

Kapusta

2023

Applied Sciences

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There are several possibilities to improve classification in natural language processing tasks. In this article, we focused on the issue of coreference resolution that was applied to a manually annotated dataset of true and fake news. This dataset was used for the classification task of fake news detection. The research aimed to determine whether performing coreference resolution on the input data before classification or classifying them without performing coreference resolution is more effective. We also wanted to verify whether it is possible to enhance classifier performance metrics by incorporating coreference resolution into the data preparation process. A methodology was proposed, in which we described the implementation methods in detail, starting from the identification of entity mentions in the text using the neuralcoref algorithm, then through word-embedding models (TF–IDF, Doc2Vec), and finally to several machine learning methods. The result was a comparison of the implemented classifiers based on the performance metrics described in the theoretical part. The best result for accuracy was observed for the dataset with coreference resolution applied, which had a median value of 0.8149, while for the F1 score, the best result had a median value of 0.8101. However, the more important finding is that the processed data with the application of coreference resolution led to an improvement in performance metrics in the classification tasks.

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“…Big Data processing is more based on distributed file systems and distributed computing than just database storage and querying, enabling real-time data, dynamic acquisition, large data storage, and massive data analysis (real-time computing, stream processing). (Wang, 2020). Considering that TikTok is a Byte Dance product, a large database is both a company's most crucial output and its most economically useful component.…”

Section: What Is Big Data?mentioning

confidence: 99%

A Study of the TikTok Business and Communication Model, Including Its Prospects and Constraints on Youth

2023

SSSH

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With the rapid development of information technology and the emergence of various digital media platforms, TikTok has gradually become known and appreciated by the public. This study aims to investigate and analyze the collective activities of young users on the TikTok platform, focusing on their profiles, TikTok’s Dissemination Model, and business models. The popularity of TikTok among the youth, especially teenagers, has made it an important platform for them to participate in cultural activities and establish their online presence. By examining existing social science research and utilizing data from TikTok, this study seeks to understand how young users engage with the platform and the role it plays in shaping their activities. Additionally, the study will explore the potential of TikTok as well as the challenges it currently faces in facilitating youth practices.

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Research on application of article recommendation algorithm based on Word2Vec and Tfidf

Cited by 9 publications

References 1 publication

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms

Coreference Resolution for Improving Performance Measures of Classification Tasks

A Study of the TikTok Business and Communication Model, Including Its Prospects and Constraints on Youth

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