Zejun Yang¹, Denghui Xia¹, Jin Liu¹, Chao Zheng², Yanzhen Qu^1,3,4, Yadang Chen¹, Chengjun Zhang^1,2,3,*

Journal on Internet of Things, Vol.3, No.2, pp. 65-76, 2021, DOI:10.32604/jiot.2021.015401 - 15 July 2021

Abstract Collaborative filtering algorithms (CF) and mass diffusion (MD) algorithms have been successfully applied to recommender systems for years and can solve the problem of information overload. However, both algorithms suffer from data sparsity, and both tend to recommend popular products, which have poor diversity and are not suitable for real life. In this paper, we propose a user internal similarity-based recommendation algorithm (UISRC). UISRC first calculates the item-item similarity matrix and calculates the average similarity between items purchased by each user as the user’s internal similarity. The internal similarity of users is combined to modify More >

Li Li¹, Chen Cui^1,2, Jianfeng Lu¹, Shanqing Zhang^1,*, Ching-Chun Chang³

Computer Systems Science and Engineering, Vol.38, No.3, pp. 291-303, 2021, DOI:10.32604/csse.2021.016340 - 19 May 2021

Abstract As an efficient technique for anti-counterfeiting, holographic diffraction labels has been widely applied to various fields. Due to their unique feature, traditional image recognition algorithms are not ideal for the holographic diffraction label recognition. Since a tensor preserves the spatiotemporal features of an original sample in the process of feature extraction, in this paper we propose a new holographic diffraction label recognition algorithm that combines two tensor features. The HSV (Hue Saturation Value) tensor and the HOG (Histogram of Oriented Gradient) tensor are used to represent the color information and gradient information of holographic diffraction… More >

Ramsha Saeed¹, Saddaf Rubab¹, Sara Asif¹, Malik M. Khan¹, Saeed Murtaza¹, Seifedine Kadry², Yunyoung Nam^3,*, Muhammad Attique Khan^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 533-547, 2021, DOI:10.32604/cmes.2021.014355 - 19 April 2021

Abstract The substantial competition among the news industries puts editors under the pressure of posting news articles which are likely to gain more user attention. Anticipating the popularity of news articles can help the editorial teams in making decisions about posting a news article. Article similarity extracted from the articles posted within a small period of time is found to be a useful feature in existing popularity prediction approaches. This work proposes a new approach to estimate the popularity of news articles by adding semantics in the article similarity based approach of popularity estimation. A semantically More >

Miguel-Angel Sicilia^1,*, Elena García-Barriocanal¹, Marçal Mora-Cantallops¹, Salvador Sánchez-Alonso¹, Lino González²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1661-1672, 2021, DOI:10.32604/cmc.2021.015874 - 13 April 2021

Abstract Existing studies have challenged the current definition of named bacterial species, especially in the case of highly recombinogenic bacteria. This has led to considering the use of computational procedures to examine potential bacterial clusters that are not identified by species naming. This paper describes the use of sequence data obtained from MLST databases as input for a k-means algorithm extended to deal with housekeeping gene sequences as a metric of similarity for the clustering process. An implementation of the k-means algorithm has been developed based on an existing source code implementation, and it has been More >

Rahmat Hidayat^1,2,*, Iwan Tri Riyadi Yanto^1,3, Azizul Azhar Ramli¹, Mohd Farhan Md. Fudzee¹, Ansari Saleh Ahmar⁴

Computer Systems Science and Engineering, Vol.38, No.1, pp. 119-130, 2021, DOI:10.32604/csse.2021.015628 - 01 April 2021

Abstract

Classification is one of the data mining processes used to predict predetermined target classes with data learning accurately. This study discusses data classification using a fuzzy soft set method to predict target classes accurately. This study aims to form a data classification algorithm using the fuzzy soft set method. In this study, the fuzzy soft set was calculated based on the normalized Hamming distance. Each parameter in this method is mapped to a power set from a subset of the fuzzy set using a fuzzy approximation function. In the classification step, a generalized normalized Euclidean

… More >

Tahir Mahmood¹, Wajid Ali¹, Zeeshan Ali¹, Ronnason Chinram^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1165-1187, 2021, DOI:10.32604/cmes.2021.014393 - 19 February 2021

Abstract Intuitionistic hesitant fuzzy set (IHFS) is a mixture of two separated notions called intuitionistic fuzzy set (IFS) and hesitant fuzzy set (HFS), as an important technique to cope with uncertain and awkward information in realistic decision issues. IHFS contains the grades of truth and falsity in the form of the subset of the unit interval. The notion of IHFS was defined by many scholars with different conditions, which contain several weaknesses. Here, keeping in view the problems of already defined IHFSs, we will define IHFS in another way so that it becomes compatible with other… More >

Kashif Irshad¹, Muhammad Tanvir Afzal², Sanam Shahla Rizvi³, Abdul Shahid⁴, Rabia Riaz⁵, Tae-Sun Chung^6,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 877-894, 2021, DOI:10.32604/cmc.2021.014156 - 12 January 2021

Abstract The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret… More >

Fan Zhang^1,2, Fenlin Liu^1,2,*, Rui Xu^3,4, Xiangyang Luo^1,2, Shichang Ding⁵, Hechan Tian^1,2

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3345-3361, 2021, DOI:10.32604/cmc.2021.014526 - 28 December 2020

Abstract Existing IP geolocation algorithms based on delay similarity often rely on the principle that geographically adjacent IPs have similar delays. However, this principle is often invalid in real Internet environment, which leads to unreliable geolocation results. To improve the accuracy and reliability of locating IP in real Internet, a street-level IP geolocation algorithm based on landmarks clustering is proposed. Firstly, we use the probes to measure the known landmarks to obtain their delay vectors, and cluster landmarks using them. Secondly, the landmarks are clustered again by their latitude and longitude, and the intersection of these… More >

Muhammad Yahya Saeed¹, Muhammad Awais¹, Muhammad Younas¹, Muhammad Arif Shah^2,*, Atif Khan³, M. Irfan Uddin⁴, Marwan Mahmoud⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2409-2423, 2021, DOI:10.32604/cmc.2021.014330 - 28 December 2020

Abstract Text Summarization is an essential area in text mining, which has procedures for text extraction. In natural language processing, text summarization maps the documents to a representative set of descriptive words. Therefore, the objective of text extraction is to attain reduced expressive contents from the text documents. Text summarization has two main areas such as abstractive, and extractive summarization. Extractive text summarization has further two approaches, in which the first approach applies the sentence score algorithm, and the second approach follows the word embedding principles. All such text extractions have limitations in providing the basic… More >

Yunping Zhao¹, Weixuan Liang¹, Jianzhuang Lu^1,*, Xiaowen Chen¹, Nijiwa Kong²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2709-2722, 2021, DOI:10.32604/cmc.2021.013389 - 28 December 2020

Abstract Late fusion multi-view clustering (LFMVC) algorithms aim to integrate the base partition of each single view into a consensus partition. Base partitions can be obtained by performing kernel k-means clustering on all views. This type of method is not only computationally efficient, but also more accurate than multiple kernel k-means, and is thus widely used in the multi-view clustering context. LFMVC improves computational efficiency to the extent that the computational complexity of each iteration is reduced from O(n³) to O(n) (where n is the number of samples). However, LFMVC also limits the search space of the… More >