K. Chitra^*, A. Tamilarasi

Computer Systems Science and Engineering, Vol.44, No.1, pp. 327-337, 2023, DOI:10.32604/csse.2023.023920

Abstract The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems. Social Media platforms were initially developed for effective communication, but now it is being used widely for extending and to obtain profit among business community. The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it. A giant network of people in social media is grouped together based on their similar properties to form a community. Community detection is recent topic among the research community due to the increase usage of… More >

Yujiang Li^1,2, Chun Ding^1,2, Zhili Zhou^1,2,*

Journal of New Media, Vol.4, No.1, pp. 51-58, 2022, DOI:10.32604/jnm.2022.028775

Abstract With the development of new media technology, vehicle matching plays a further significant role in video surveillance systems. Recent methods explored the vehicle matching based on the feature extraction. Meanwhile, similarity metric learning also has achieved enormous progress in vehicle matching. But most of these methods are less effective in some realistic scenarios where vehicles usually be captured in different times. To address this cross-domain problem, we propose a cross-domain similarity metric learning method that utilizes the GAN to generate vehicle images with another domain and propose the two-channel Siamese network to learn a similarity metric from both domains (i.e.,… More >

Debasis Mohapatra¹, Sourav Kumar Bhoi¹, Kalyan Kumar Jena¹, Chittaranjan Mallick², Kshira Sagar Sahoo³, N. Z. Jhanjhi^4,*, Mehedi Masud⁵

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 51-64, 2022, DOI:10.32604/iasc.2022.024561

Abstract Most of the recent works on network science are focused on investigating various interactions among a set of entities present in a system that can be represented by multiplex network. Each type of relationship is treated as a layer of multiplex network. Some of the recent works on multiplex networks are focused on deriving layer similarity from node similarity where node similarity is evaluated using neighborhood similarity measures like cosine similarity and Jaccard similarity. But this type of analysis lacks in finding the set of nodes having the same influence in both the network. The discovery of influence similarity between… More >

S. Manikandan^1,*, P. Dhanalakshmi², K. C. Rajeswari³, A. Delphin Carolina Rani⁴

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 183-192, 2022, DOI:10.32604/iasc.2022.023469

Abstract The similarity recommendation of twitter data is evaluated by using sentiment analysis method. In this paper, the deep learning processes such as classification, clustering and prediction are used to measure the data. Convolutional neural network is applied for analyzing multimedia contents which is received from various sources. Recurrent neural network is used for handling the natural language data. The content based recommendation system is proposed for selecting similarity index in twitter data using deep sentiment learning method. In this paper, sentiment analysis technique is used for finding similar images, contents, texts, etc. The content is selected based on repetitive comments… More >

Xinghai Ju¹, Jicang Lu^1,*, Xiangyang Luo¹, Gang Zhou¹, Shiyu Wang¹, Shunhang Li¹, Yang Yang^2,3

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3247-3267, 2022, DOI:10.32604/cmc.2022.026698

Abstract For Internet forum Points of Interest (PoI), existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation, which lead to blindness in method selection. To address this problem, this paper proposed a PoI variation prediction framework based on similarity analysis between long and short windows. Based on the framework, this paper presented 5 PoI analysis algorithms which can be categorized into 2 types, i.e., the traditional sequence analysis methods such as autoregressive integrated moving average model (ARIMA), support vector regressor (SVR), and the deep learning methods such as convolutional neural network (CNN), long-short… More >

Ahmed M. Mostafa^*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4125-4142, 2022, DOI:10.32604/cmc.2022.024676

Abstract Many businesses have experienced difficulties in selecting a cloud service provider (CSP) due to the rapid advancement of cloud computing services and the proliferation of CSPs. Many independent criteria should be considered when evaluating the services provided by different CSPs. It is a case of multi-criteria decision-making (MCDM). This paper presents an integrated MCDM cloud service selection framework for determining the most appropriate service provider based on the best only method (BOM) and technique for order of preference by similarity to ideal solution (TOPSIS). To obtain the weights of criteria and the relative importance of CSPs based on each criterion,… More >

Amira Hamed Abo-Elghit^1,*, Taher Hamza¹, Aya Al-Zoghby²

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1967-1994, 2022, DOI:10.32604/cmc.2022.025353

Abstract Nowadays, we can use the multi-task learning approach to train a machine-learning algorithm to learn multiple related tasks instead of training it to solve a single task. In this work, we propose an algorithm for estimating textual similarity scores and then use these scores in multiple tasks such as text ranking, essay grading, and question answering systems. We used several vectorization schemes to represent the Arabic texts in the SemEval2017-task3-subtask-D dataset. The used schemes include lexical-based similarity features, frequency-based features, and pre-trained model-based features. Also, we used contextual-based embedding models such as Arabic Bidirectional Encoder Representations from Transformers (AraBERT). We… More >

Jayavarthini Chockalingam^*, Malathy Chidambaranathan

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 697-710, 2022, DOI:10.32604/iasc.2022.024142

Abstract Presently, Person Re-IDentification (PRe-ID) acts as a vital part of real time video surveillance to ensure the rising need for public safety. Resolving the PRe-ID problem includes the process of matching observations of persons among distinct camera views. Earlier models consider PRe-ID as a unique object retrieval issue and determine the retrieval results mainly based on the unidirectional matching among the probe and gallery images. But the accurate matching might not be present in the top-k ranking results owing to the appearance modifications caused by the difference in illumination, pose, viewpoint, and occlusion. For addressing these issues, a new Hyper-parameter… More >

S. Neelakandan^1,*, A. Arun², Raghu Ram Bhukya³, Bhalchandra M. Hardas⁴, T. Ch. Anil Kumar⁵, M. Ashok⁶

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1617-1632, 2022, DOI:10.32604/iasc.2022.022209

Abstract In recent years, web crawling has gained a significant attention due to the drastic advancements in the World Wide Web. Web Search Engines have the issue of retrieving massive quantity of web documents. One among the web crawlers is the focused crawler, that intends to selectively gather web pages from the Internet. But the efficiency of the focused crawling can easily be affected by the environment of web pages. In this view, this paper presents an Automated Word Embedding with Parameter Tuned Deep Learning (AWE-PTDL) model for focused web crawling. The proposed model involves different processes namely pre-processing, Incremental Skip-gram… More >

Mengmeng Ge¹, Xiangzhan Yu^1,*, Lin Ye^1,2, Jiantao Shi¹

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3393-3405, 2022, DOI:10.32604/cmc.2022.017220

Abstract With the rapid development of the Internet, the types of webpages are more abundant than in previous decades. However, it becomes severe that people are facing more and more significant network security risks and enormous losses caused by phishing webpages, which imitate the interface of real webpages and deceive the victims. To better identify and distinguish phishing webpages, a visual feature extraction method and a visual similarity algorithm are proposed. First, the visual feature extraction method improves the Vision-based Page Segmentation (VIPS) algorithm to extract the visual block and calculate its signature by perceptual hash technology. Second, the visual similarity… More >