Arar Al Tawil^1,*, Laiali Almazaydeh², Doaa Qawasmeh³, Baraah Qawasmeh⁴, Mohammad Alshinwan^1,5, Khaled Elleithy⁶

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3395-3412, 2024, DOI:10.32604/cmc.2024.057279 - 18 November 2024

Abstract Cybercriminals often use fraudulent emails and fictitious email accounts to deceive individuals into disclosing confidential information, a practice known as phishing. This study utilizes three distinct methodologies, Term Frequency-Inverse Document Frequency, Word2Vec, and Bidirectional Encoder Representations from Transformers, to evaluate the effectiveness of various machine learning algorithms in detecting phishing attacks. The study uses feature extraction methods to assess the performance of Logistic Regression, Decision Tree, Random Forest, and Multilayer Perceptron algorithms. The best results for each classifier using Term Frequency-Inverse Document Frequency were Multilayer Perceptron (Precision: 0.98, Recall: 0.98, F1-score: 0.98, Accuracy: 0.98). Word2Vec’s More >

Milos Dobrojevic^1,4, Luka Jovanovic¹, Lepa Babic³, Miroslav Cajic⁵, Tamara Zivkovic⁶, Miodrag Zivkovic², Suresh Muthusamy⁷, Milos Antonijevic², Nebojsa Bacanin^2,4,8,9,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4997-5027, 2024, DOI:10.32604/cmc.2024.054459 - 12 September 2024

Abstract Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones, computers, or tablets. It can occur through various channels, such as social media, text messages, online forums, or gaming platforms. Cyberbullying involves using technology to intentionally harm, harass, or intimidate others and may take different forms, including exclusion, doxing, impersonation, harassment, and cyberstalking. Unfortunately, due to the rapid growth of malicious internet users, this social phenomenon is becoming more frequent, and there is a huge need to address this issue. Therefore, the main goal of the research… More >

Ahmad Ababneh¹, Yousef Sanjalawe², Salam Fraihat^3,*, Salam Al-E’mari⁴, Hamzah Alqudah⁵

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1347-1379, 2024, DOI:10.32604/cmc.2024.050600 - 18 July 2024

Abstract This study introduces the Orbit Weighting Scheme (OWS), a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval (IR) models, which have traditionally relied on weighting schemes like tf-idf and BM25. These conventional methods often struggle with accurately capturing document relevance, leading to inefficiencies in both retrieval performance and index size management. OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space, emphasizing term relationships and distribution patterns overlooked by existing models. Our research focuses on evaluating OWS’s impact… More >

Badriyya B. Al-onazi¹, Jaber S. Alzahrani², Najm Alotaibi³, Hussain Alshahrani⁴, Mohamed Ahmed Elfaki⁴, Radwa Marzouk⁵, Heba Mohsen⁶, Abdelwahed Motwakel^7,*

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 567-583, 2024, DOI:10.32604/iasc.2023.033835 - 11 July 2024

Abstract In recent years, the usage of social networking sites has considerably increased in the Arab world. It has empowered individuals to express their opinions, especially in politics. Furthermore, various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different scales. This is attributed to business owners’ understanding of social media’s importance for business development. However, the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and nouns. Hate speech… More >

Siyu Lu¹, Ligao Cai¹, Zhixin Liu², Shan Liu¹, Bo Yang¹, Lirong Yin³, Mingzhe Liu⁴, Wenfeng Zheng^1,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1881-1899, 2023, DOI:10.32604/csse.2023.034853 - 28 July 2023

Abstract With the development of Internet technology, the explosive growth of Internet information presentation has led to difficulty in filtering effective information. Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering, especially for Chinese texts. This paper selected the manually calibrated Douban movie website comment data for research. First, a text filtering model based on the BP neural network has been built; Second, based on the Term Frequency-Inverse Document Frequency (TF-IDF) vector space model and the doc2vec method, the text word frequency vector and the More >

Fahriye Gemci^1,*, Turgay Ibrikci², Ulus Cevik³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3703-3713, 2023, DOI:10.32604/csse.2023.032706 - 03 April 2023

Abstract The study aims to find a successful solution by using computer algorithms to detect remote homologous proteins, which is a significant problem in the bioinformatics field. In this experimental study, structural classification of proteins (SCOP) 1.53, SCOP benchmark, and the newly created SCOP protein database from the structural classification of proteins—extended (SCOPe) 2.07 were used to detect remote homolog proteins. N-gram method and then Term Frequency-Inverse Document Frequency (TF-IDF) weighting were performed to extract features of the protein sequences taken from these databases. Next, a smoothing process on the obtained features was performed to avoid… More >

Hanxu Wang, Xin Li^*

Journal on Big Data, Vol.4, No.1, pp. 41-60, 2022, DOI:10.32604/jbd.2022.027717 - 04 May 2022

Abstract With the explosive growth of Internet text information, the task of text classification is more important. As a part of text classification, Chinese news text classification also plays an important role. In public security work, public opinion news classification is an important topic. Effective and accurate classification of public opinion news is a necessary prerequisite for relevant departments to grasp the situation of public opinion and control the trend of public opinion in time. This paper introduces a combined-convolutional neural network text classification model based on word2vec and improved TF-IDF: firstly, the word vector is… More >

Zhuo Zhou¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Qiang Liu¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 217-231, 2020, DOI:10.32604/cmc.2020.06431

Abstract Due to the slow processing speed of text topic clustering in stand-alone architecture under the background of big data, this paper takes news text as the research object and proposes LDA text topic clustering algorithm based on Spark big data platform. Since the TF-IDF (term frequency-inverse document frequency) algorithm under Spark is irreversible to word mapping, the mapped words indexes cannot be traced back to the original words. In this paper, an optimized method is proposed that TF-IDF under Spark to ensure the text words can be restored. Firstly, the text feature is extracted by More >