Optimal Dependence of Performance and Efficiency of Collaborative Filtering on Random Stratified Subsampling by Samin Poudel, Marwan Bikdash

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Selected Topics on Perspectives in Business Informatics Research: Editorial Introduction to the Issue 14 of CSIMQ by Björn Johansson, Charles Møller

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A Recommendation Model Using the Bandwagon Effect for E-Marketing Purposes in IoT by Sang-Min Choi, Hyein Lee, Yo-Sub Han, Ka Lok Man, Woon Kian Chong

“…A personalized recommender system often relies on user preferences for better suggestions. …”
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A security detection approach based on autonomy-oriented user sensor in social recommendation network by Shanshan Wan, Ying Liu

“…User social network-based recommender system has achieved significant performance in current recommendation fields. …”
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A Novel Preferential Diffusion Recommendation Algorithm Based on User’s Nearest Neighbors by Fuguo Zhang, Yehuan Liu, Qinqiao Xiong

“…Recommender system is a very efficient way to deal with the problem of information overload for online users. …”
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Utilizing Structural Network Positions to Diversify People Recommendations on Twitter by Ekaterina Olshannikova, Erjon Skenderi, Thomas Olsson, Sami Koivunen, Jukka Huhtamäki

“…Social recommender systems, such as “Who to follow” on Twitter, utilize approaches that recommend friends of a friend or interest-wise similar people. …”
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Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation by Kashif Zia, Arshad Muhammad, Abbas Khalid, Ahmad Din, Alois Ferscha

“…The simulation results reveal that closure of social ties and its timing impacts the dispersion of novel information (necessary for a recommender system) substantially. It is also observed that as the network evolves due to incremental interactions, the recommendations guaranteeing a fair distribution of vehicles across equally good competitors is not possible.…”
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GAN inversion and shifting: recommending product modifications to sellers for better user preference by Satyadwyoom Kumar, Abhijith Sharma, Apurva Narayan

“…This exploration has given rise to recommendation systems, which utilize customer similarity with other customers or customer-item interactions to suggest new items based on the existing item catalog. …”
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A Joint Deep Recommendation Framework for Location-Based Social Networks by Omer Tal, Yang Liu

“…By providing such service, point-of-interest recommender systems have attracted much interest from different societies, leading to improved methods and techniques. …”
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Next-generation diabetes diagnosis and personalized diet-activity management: A hybrid ensemble paradigm. by Muhammad Sajid, Kaleem Razzaq Malik, Ali Haider Khan, Sajid Iqbal, Abdullah A Alaulamie, Qazi Mudassar Ilyas

“…Furthermore, a thorough food and exercise recommender system is unveiled, offering individualized and health-conscious nutrition recommendations based on user preferences and medical information. …”
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Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation by Zhao Li, Haobo Wang, Donghui Ding, Shichang Hu, Zhen Zhang, Weiwei Liu, Jianliang Gao, Zhiqiang Zhang, Ji Zhang

“…To this end, an E-commerce platform Taobao launched a fresh-item hub page on the recommender system, with which customers can freely and exclusively explore and purchase fresh items, namely, the New Tendency page. …”
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Solusi untuk Meningkatkan Knowledge Management Readness di Badan Pusat Statistik Kabupaten/Kota by Herlambang Permadi, Dana Indra Sensuse

“…From the results of this analysis, a tool design was proposed as a recommendation to solve these problems, including an online survey system environment to help reduce workloads, and an employee placement recommender system using Analytical Hierarchy Process (AHP) to assist employee mapping. …”
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Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms by HongYan Liang

“…In addition, this paper constructs an intelligent recommendation system based on the actual needs of travel recommendation and verifies the system in combination with experimental research. …”
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Integrating Pull Request Comment Analysis and Developer Profiles for Expertise-Based Recommendations in Global Software Development by Sara Zamir, Abdul Rehman, Hufsa Mohsin, Elif Zamir, Assad Abbas, Fuad A. M. Al-Yarimi

“…This research intends to create a recommendation system using pull request review comments and selected data from developers’ profiles to recommend better experts based on their dynamic expertise. …”
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Personalized Recommendation of Online Shopping Products Based on Online Fast Learning through Latent Factor Model by Meng Shi

“…In order to improve the personalized recommendation effect of online shopping products, this article combines online fast learning through latent factor model to construct a personalized virtual planning recommendation system for online shopping products. Moreover, this article improves on the ONMTF model. …”
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Hidden Markov model fused with staying time for personalized recommendation by Sheng-zong LIU, Xiao-ping FAN, Zhi-fang LIAO, Jia HU

“…Static model in the recommendation system often regards the user's interest as changeless,which is inconsis-tent with the actual to a certain extent.With regards to this,a hidden Markov model fused with staying time for personal-ized recommendation (ctqHMM) based on the HMM dynamic model is proposed.The proposed model employs the transfer of the implicit state variables to simulate the changes of Web users' interests,and uses staying time to describe the level of interest to the specific preference and the importance of the recommended pages.Then,a user's clustering method based on the stationary distribution of the ctqHMM is also proposed and applied into the recommending systems.Experiment results on real Web server access log data show the encouraging performance of the proposed method over the state-of-the-arts.…”
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A Study on Multiattribute Aggregation Approaches to Product Recommendation by Jing-Zhong Jin, Yoshiteru Nakamori, Andrzej P. Wierzbicki

“…To test the aggregation models and the ranking methods, a recommendation system was developed and a comparison test was conducted.…”
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Information Filtering via Biased Random Walk on Coupled Social Network by Da-Cheng Nie, Zi-Ke Zhang, Qiang Dong, Chongjing Sun, Yan Fu

“…The recommender systems have advanced a great deal in the past two decades. …”
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The Prefiltering Techniques in Emotion Based Place Recommendation Derived by User Reviews by U. A. Piumi Ishanka, Takashi Yukawa

“…Context-aware recommendation systems attempt to address the challenge of identifying products or items that have the greatest chance of meeting user requirements by adapting to current contextual information. …”
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A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features by Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri

“…<italic>Goal:</italic> The purpose of this study is to evaluate the importance of cardiorespiratory variables within a Reinforcement Learning (RL) recommendation system aimed at establishing optimal strategies for drug treatment of septic patients in the intensive care unit (ICU). …”
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