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Songlin Tian, Ying Yang and Lei Yang
Business intelligence (BI), as a system for business data integration, processing, and analysis, is receiving increasing attention from enterprises. Data visualization is an important feature of BI, which allows users to visually observe the distribution...
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Deepanjal Shrestha, Tan Wenan, Deepmala Shrestha, Neesha Rajkarnikar and Seung-Ryul Jeong
This study introduces a data-driven and machine-learning approach to design a personalized tourist recommendation system for Nepal. It examines key tourist attributes, such as demographics, behaviors, preferences, and satisfaction, to develop four sub-mo...
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Dimitris Mpouziotas, Jeries Besharat, Ioannis G. Tsoulos and Chrysostomos Stylios
AliAmvra is a project developed to explore and promote high-quality catches of the Amvrakikos Gulf (GP) to Artas? wider regions. In addition, this project aimed to implement an integrated plan of action to form a business identity with high added value a...
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Bin Cheng, Ping Chen, Xin Zhang, Keyu Fang, Xiaoli Qin and Wei Liu
With the rapid development of ubiquitous data collection and data analysis, data privacy in a recommended system is facing more and more challenges. Differential privacy technology can provide strict privacy protection while reducing the risk of privacy ...
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Yuanyou Ou and Baoning Niu
The dual-channel graph collaborative filtering recommendation algorithm (DCCF) suppresses the over-smoothing problem and overcomes the problem of expansion in local structures only in graph collaborative filtering. However, DCCF has the following problem...
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Dharahas Tallapally, John Wang, Katerina Potika and Magdalini Eirinaki
Recommender systems have revolutionized the way users discover and engage with content. Moving beyond the collaborative filtering approach, most modern recommender systems leverage additional sources of information, such as context and social network dat...
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Yunfei Zhang, Hongzhen Xu and Xiaojun Yu
An improved recommendation algorithm based on Conditional Variational Autoencoder (CVAE) and Constrained Probabilistic Matrix Factorization (CPMF) is proposed to address the issues of poor recommendation performance in traditional user-based collaborativ...
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Loris Belcastro, Domenico Carbone, Cristian Cosentino, Fabrizio Marozzo and Paolo Trunfio
Since the advent of Bitcoin, the cryptocurrency landscape has seen the emergence of several virtual currencies that have quickly established their presence in the global market. The dynamics of this market, influenced by a multitude of factors that are d...
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Abdelrhman Eldallal and Eduard Barbu
Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks, such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. ...
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Chin-Yi Chen and Jih-Jeng Huang
Traditional movie recommendation systems are increasingly falling short in the contemporary landscape of abundant information and evolving user behaviors. This study introduced the temporal knowledge graph recommender system (TKGRS), a ground-breaking al...
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