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Citations to this Journal [246 citations: 1–100 of 246 articles]

Articles published in Advances in Artificial Intelligence have been cited 246 times. The following is a list of the 246 articles that have cited the articles published in Advances in Artificial Intelligence.

  • Suwoong Lee, Hidetaka Nozawa, Daisuke Watanabe, and Kenji Inoue, “Force estimation via physical properties of air cushion for the control of a human-cooperative robot: basic experiments,” Advanced Robotics, vol. 29, no. 2, pp. 139–146, 2015. View at Publisher · View at Google Scholar
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  • Krishna Chaitanya Patchava, Mohammed Benaissa, Bilal Malik, and Hatim Behairy, “Local linear embedded regression in the quantitative analysis of glucose in near infrared spectra,” Analytical Methods, vol. 7, no. 4, pp. 1484–1492, 2015. View at Publisher · View at Google Scholar
  • Faezeh S. Gohari, and Mohammad Jafar Tarokh, “New Recommender Framework: Combining Semantic Similarity Fusion and Bicluster Collaborative Filtering,” Computational Intelligence, 2015. View at Publisher · View at Google Scholar
  • Duy Vu, and Murray Aitkin, “Variational algorithms for biclustering models,” Computational Statistics & Data Analysis, 2015. View at Publisher · View at Google Scholar
  • Edward Rolando Núñez-Valdez, Juan Manuel Cueva Lovelle, Guillermo Infante Hernández, Aquilino Juan Fuente, and José Emilio Labra-Gayo, “Creating recommendations on electronic books: A collaborative learning implicit approach,” Computers in Human Behavior, 2015. View at Publisher · View at Google Scholar
  • Francesco Colace, Massimo De Santo, Luca Greco, Vincenzo Moscato, and Antonio Picariello, “A collaborative user-centered framework for recommending items in Online Social Networks,” Computers in Human Behavior, 2015. View at Publisher · View at Google Scholar
  • Vincenza Carchiolo, Alessandro Longheu, Michele Malgeri, and Giuseppe Mangioni, “Searching for experts in a context-aware recommendation network,” Computers in Human Behavior, 2015. View at Publisher · View at Google Scholar
  • Antoine Boutet, Davide Frey, Rachid Guerraoui, Arnaud Jégou, and Anne-Marie Kermarrec, “Privacy-preserving distributed collaborative filtering,” Computing, 2015. View at Publisher · View at Google Scholar
  • Huiji Gao, Jiliang Tang, and Huan Liu, “Addressing the cold-start problem in location recommendation using geo-social correlations,” Data Mining And Knowledge Discovery, vol. 29, no. 2, pp. 299–323, 2015. View at Publisher · View at Google Scholar
  • Malak Al-Hassan, Haiyan Lu, and Jie Lu, “A Semantic Enhanced Hybrid Recommendation Approach: a Case Study of E-government Tourism Service Recommendation System,” Decision Support Systems, 2015. View at Publisher · View at Google Scholar
  • Ying-Si Zhao, Yan-Ping Liu, and Qing-An Zeng, “A weight-based item recommendation approach for electronic commerce systems,” Electronic Commerce Research, 2015. View at Publisher · View at Google Scholar
  • Yueshen Xu, and Jianwei Yin, “Collaborative recommendation with user generated content,” Engineering Applications of Artificial Intelligence, vol. 45, pp. 281–294, 2015. View at Publisher · View at Google Scholar
  • Santiago Cifuentes, Jose María Girón-Sierra, and Juan Jiménez, “Virtual fields and behaviour blending for the coordinated navigation of robot teams: Some experimental results.,” Expert Systems with Applications, 2015. View at Publisher · View at Google Scholar
  • Anupriya Gogna, and Angshul Majumdar, “Matrix Completion Incorporating Auxiliary Information for Recommender System Design,” Expert Systems with Applications, 2015. View at Publisher · View at Google Scholar
  • Parham Moradi, and Sajad Ahmadian, “A reliability-based recommendation method to improve trust-aware recommender systems,” Expert Systems with Applications, 2015. View at Publisher · View at Google Scholar
  • Dimah H. Alahmadi, and Xaio-Jun Zeng, “ISTS: Implicit Social Trust and Sentiment based Approach to Recommender Systems,” Expert Systems with Applications, 2015. View at Publisher · View at Google Scholar
  • David Silvera-Tawil, David Rye, Manuchehr Soleimani, and Mari Velonaki, “Electrical Impedance Tomography for Artificial Sensitive Robotic Skin: A Review,” Ieee Sensors Journal, vol. 15, no. 4, pp. 2001–2016, 2015. View at Publisher · View at Google Scholar
  • Anna Cinzia Squicciarini, Dan Lin, Smitha Sundareswaran, and Joshua Wede, “Privacy Policy Inference of User-Uploaded Images on Content Sharing Sites,” Ieee Transactions On Knowledge And Data Engineering, vol. 27, no. 1, pp. 193–206, 2015. View at Publisher · View at Google Scholar
  • Nicholas Jing Yuan, Yu Zheng, Xing Xie, Yingzi Wang, Kai Zheng, and Hui Xiong, “Discovering Urban Functional Zones Using Latent Activity Trajectories,” Ieee Transactions On Knowledge And Data Engineering, vol. 27, no. 3, pp. 712–725, 2015. View at Publisher · View at Google Scholar
  • Hao Wang, and Wu-Jun Li, “Relational Collaborative Topic Regression for Recommender Systems,” Ieee Transactions On Knowledge And Data Engineering, vol. 27, no. 5, pp. 1343–1355, 2015. View at Publisher · View at Google Scholar
  • Haiqin Yang, Guang Ling, Yuxin Su, Michael R. Lyu, and Irwin King, “Boosting Response Aware Model-Based Collaborative Filtering,” Ieee Transactions On Knowledge And Data Engineering, vol. 27, no. 8, pp. 2064–2077, 2015. View at Publisher · View at Google Scholar
  • Zhanyu Ma, Andrew E. Teschendorff, Arne Leijon, Yuanyuan Qiao, Honggang Zhang, and Jun Guo, “Variational Bayesian Matrix Factorization for Bounded Support Data,” Ieee Transactions On Pattern Analysis And Machine Intelligence, vol. 37, no. 4, pp. 876–889, 2015. View at Publisher · View at Google Scholar
  • Marin Silic, Goran Delac, and Sinisa Srbljic, “Prediction of Atomic Web Services Reliability for QoS-Aware Recommendation,” Ieee Transactions On Services Computing, vol. 8, no. 3, pp. 425–438, 2015. View at Publisher · View at Google Scholar
  • Lina Yao, Quan Z. Sheng, Anne. H. H. Ngu, Jian Yu, and Aviv Segev, “Unified Collaborative and Content-Based Web Service Recommendation,” Ieee Transactions On Services Computing, vol. 8, no. 3, pp. 453–466, 2015. View at Publisher · View at Google Scholar
  • Ye Wu, and Fuji Ren, “Exploiting opinion distribution for topic recommendation in twitter,” IEEJ Transactions on Electrical and Electronic Engineering, 2015. View at Publisher · View at Google Scholar
  • Chen Chen, Chunyan Hou, Peng Nie, and Xiaojie Yuan, “Personalized Recommendation of Item Category Using Ranking on Time-Aware Graphs,” Ieice Transactions On Information And Systems, vol. E98D, no. 4, pp. 948–954, 2015. View at Publisher · View at Google Scholar
  • Mohamad-Hoseyn Sigari, Hamid Soltanian-Zadeh, and Hamid-Reza Pourreza, “A Framework for Dynamic Restructuring of Semantic Video Analysis Systems Based on Learning Attention Control,” Image and Vision Computing, 2015. View at Publisher · View at Google Scholar
  • Chunyang Ma, Yongluan Zhou, Lidan Shou, and Gang Chen, “PROM: Efficient Matching Query Processing on High-dimensional Data,” Information Sciences, 2015. View at Publisher · View at Google Scholar
  • Abhijeet Ghoshal, Syam Menon, and Sumit Sarkar, “Recommendations Using Information from Multiple Association Rules: A Probabilistic Approach,” Information Systems Research, pp. 150731110323002, 2015. View at Publisher · View at Google Scholar
  • Jingang Wang, Jie Yang, and Ruixi Luo, “Non-contact transient high-voltage measurement with self-integrating D-dot probe,” International Journal Of Applied Electromagnetics And Mechanics, vol. 47, no. 3, pp. 837–845, 2015. View at Publisher · View at Google Scholar
  • Dimah Alahmadi, and Xaio-Jun Zeng, “Improving Recommendation Using Trust and Sentiment Inference from OSNs,” International Journal of Knowledge Engineering-IACSIT, vol. 1, no. 1, pp. 9–17, 2015. View at Publisher · View at Google Scholar
  • Fei Wang, “Adaptive Semi-Supervised Recursive Tree Partitioning: The ART Towards Large Scale Patient Indexing in Personalized Healthcare,” Journal of Biomedical Informatics, 2015. View at Publisher · View at Google Scholar
  • Abdusselam Altunkaynak, and Tewodros Assefa Nigussie, “Performance Comparison of SAS-Multilayer Perceptron and Wavelet-Multilayer Perceptron Models in Terms of Daily Streamflow Prediction,” Journal of Hydrologic Engineering, pp. 04015051, 2015. View at Publisher · View at Google Scholar
  • G. M. L. Sarne, “A novel hybrid approach improving effectiveness of recommender systems,” Journal Of Intelligent Information Systems, vol. 44, no. 3, pp. 397–414, 2015. View at Publisher · View at Google Scholar
  • Waleed M. Al-Adrousy, Hesham A. Ali, and Taher T. Hamza, “A recommender system for team formation in MANET,” Journal of King Saud University - Computer and Information Sciences, 2015. View at Publisher · View at Google Scholar
  • I-Chin Wu, and Yun-Fang Niu, “Effects of anchoring process under preference stabilities for interactive movie recommendations,” Journal of the Association for Information Science and Technology, 2015. View at Publisher · View at Google Scholar
  • Faris Alqadah, Chandan K. Reddy, Junling Hu, and Hatim F. Alqadah, “Biclustering neighborhood-based collaborative filtering method for top-n recommender systems,” Knowledge And Information Systems, vol. 44, no. 2, pp. 475–491, 2015. View at Publisher · View at Google Scholar
  • Ingrid Nunes, Simon Miles, Michael Luck, and Carlos J. P. Lucena, “An introduction to reasoning over qualitative multi-attribute preferences,” Knowledge Engineering Review, vol. 30, no. 3, pp. 342–372, 2015. View at Publisher · View at Google Scholar
  • Bidyut Kr. Patra, Raimo Launonen, Ville Ollikainen, and Sukumar Nandi, “A new similarity measure using Bhattacharyya coefficient for collaborative filtering in sparse data,” Knowledge-Based Systems, 2015. View at Publisher · View at Google Scholar
  • Ke Ji, Runyuan Sun, Wenhao Shu, and Xiang Li, “Next-song Recommendation with Temporal Dynamics,” Knowledge-Based Systems, 2015. View at Publisher · View at Google Scholar
  • Heng-Ru Zhang, Fan Min, Xu He, and Yuan-Yuan Xu, “A Hybrid Recommender System Based on User-Recommender Interaction,” Mathematical Problems in Engineering, vol. 2015, pp. 1–11, 2015. View at Publisher · View at Google Scholar
  • Wei Zhou, Junhao Wen, Min Gao, Haijun Ren, and Peng Li, “Abnormal Profiles Detection Based on Time Series and Target Item Analysis for Recommender Systems,” Mathematical Problems in Engineering, vol. 2015, pp. 1–9, 2015. View at Publisher · View at Google Scholar
  • Solvi Arnold, Reiji Suzuki, and Takaya Arita, “Selection for Representation in Higher-Order Adaptation,” Minds and Machines, 2015. View at Publisher · View at Google Scholar
  • Ke Ji, and Hong Shen, “Making Recommendations From Top-N User-Item Subgroups,” Neurocomputing, 2015. View at Publisher · View at Google Scholar
  • Joanne L. Park, Malcolm M. Fairweather, and David I. Donaldson, “Making the case for mobile cognition: EEG and sports performance,” Neuroscience & Biobehavioral Reviews, 2015. View at Publisher · View at Google Scholar
  • Susanna Alloisio, Mario Nobile, and Antonio Novellino, “Multiparametric characterization of neuronal network activity for in vitro agrochemical neurotoxicity assessment,” NeuroToxicology, 2015. View at Publisher · View at Google Scholar
  • Haifeng Liu, Xiaomei Bai, Zhuo Yang, Amr Tolba, and Feng Xia, “Trust-aware recommendation for improving aggregate diversity,” New Review of Hypermedia and Multimedia, pp. 1–17, 2015. View at Publisher · View at Google Scholar
  • P. L. Mazzeo, P. Spagnolo, M. Leo, T. De Marco, and C. Distante, “Ball detection in soccer images using isophote’s curvature and discriminative features,” Pattern Analysis and Applications, 2015. View at Publisher · View at Google Scholar
  • Bingrui Geng, Lingling Li, Licheng Jiao, Maoguo Gong, Qing Cai, and Yue Wu, “NNIA-RS: A multi-objective optimization based recommender system,” Physica A: Statistical Mechanics and its Applications, 2015. View at Publisher · View at Google Scholar
  • Parham Moradi, Sajad Ahmadian, and Fardin Akhlaghian, “An effective trust-based recommendation method using a novel graph clustering algorithm,” Physica A: Statistical Mechanics and its Applications, 2015. View at Publisher · View at Google Scholar
  • Meen Chul Kim, and Chaomei Chen, “A scientometric review of emerging trends and new developments in recommendation systems,” Scientometrics, vol. 104, no. 1, pp. 239–263, 2015. View at Publisher · View at Google Scholar
  • Matti Kinnunen, Salman Mian, Harri Oinas-Kukkonen, Jukka Riekki, Mirjami Jutila, Mari Ervasti, Petri Ahokangas, and Esko Alasaarela, “Wearable and mobile sensors connected to social media in human well-being applications,” Telematics and Informatics, 2015. View at Publisher · View at Google Scholar
  • Yanci Zhang, Xiaodong Che, Yu Niu, Bin Shui, Jianbo Fu, Guangzheng Fei, and Prashant Goswami, “A novel simulation framework based on information asymmetry to evaluate evacuation plan,” The Visual Computer, 2015. View at Publisher · View at Google Scholar
  • Li Chen, Guanliang Chen, and Feng Wang, “Recommender systems based on user reviews: the state of the art,” User Modeling and User-Adapted Interaction, vol. 25, no. 2, pp. 99–154, 2015. View at Publisher · View at Google Scholar
  • Nelson Capela, and Susana Sargento, “An intelligent and optimized multihoming approach in real and heterogeneous environments,” Wireless Networks, 2015. View at Publisher · View at Google Scholar
  • Kiran Ahuja, Brahmjit Singh, and Rajesh Khanna, “Optimal Network Selection in Heterogeneous Wireless Environment for Multimedia Services,” Wireless Personal Communications, 2015. View at Publisher · View at Google Scholar
  • S. Sangeetha, and T. Aruldoss Albert Victoire, “Radio Access Technology Selection in Heterogeneous Wireless Networks Using a Hybrid Fuzzy-Biogeography Based Optimization Technique,” Wireless Personal Communications, 2015. View at Publisher · View at Google Scholar
  • Shuaiqiang Wang, Jiankai Sun, Byron J. Gao, and Jun Ma, “VSRank: A Novel Framework for Ranking-Based Collaborative Filtering,” Acm Transactions On Intelligent Systems And Technology, vol. 5, no. 3, 2014. View at Publisher · View at Google Scholar
  • Soudip Roy Chowdhury, Florian Daniel, and Fabio Casati, “Recommendation and Weaving of Reusable Mashup Model Patterns for Assisted Development,” Acm Transactions on Internet Technology, vol. 14, no. 2-3, pp. 275–297, 2014. View at Publisher · View at Google Scholar
  • Alejandro Bellogin, Pablo Castells, and Ivan Cantador, “Neighbor Selection and Weighting in User-Based Collaborative Filtering: A Performance Prediction Approach,” Acm Transactions on The Web, vol. 8, no. 2, 2014. View at Publisher · View at Google Scholar
  • Anamika Yadav, and Yajnaseni Dash, “An Overview of Transmission Line Protection by Artificial Neural Network: Fault Detection, Fault Classification, Fault Location, and Fault Direction Discrimination,” Advances in Artificial Neural Systems, vol. 2014, pp. 1–20, 2014. View at Publisher · View at Google Scholar
  • S. Sasikala, S. Appavu alias Balamurugan, and S. Geetha, “Multi Filtration Feature Selection (MFFS) to improve discriminatory ability in clinical data set,” Applied Computing and Informatics, 2014. View at Publisher · View at Google Scholar
  • Pedro Henriques Abreu, Daniel Castro Silva, Fernando Almeida, and João Mendes-Moreira, “Improving a simulated soccer team's performance through a Memory-Based Collaborative Filtering approach,” Applied Soft Computing, vol. 23, pp. 180–193, 2014. View at Publisher · View at Google Scholar
  • Saravanan Sundaresan, Robin Doss, Wanlei Zhou, and Selwyn Piramuthu, “Secure Ownership Transfer for Multi-Tag Multi-Owner Passive RFID Environment with Individual-Owner-Privacy,” Computer Communications, 2014. View at Publisher · View at Google Scholar
  • Yongquan Fu, Yijie Wang, and Wei Peng, “CommonFinder: a Decentralized and Privacy-preserving Common-Friend Measurement Method for the Distributed Online Social Networks,” Computer Networks, 2014. View at Publisher · View at Google Scholar
  • Nelson Capela, and Susana Sargento, “Multihoming and network coding: A new approach to optimize the network performance,” Computer Networks, 2014. View at Publisher · View at Google Scholar
  • Sushama Karumanchi, Dan Lin, and Nicole DeSisto, “Identifying hidden social circles for advanced privacy configuration,” Computers & Security, vol. 41, pp. 40–51, 2014. View at Publisher · View at Google Scholar
  • Yongli Ren, Gang Li, and Wanlei Zhou, “A survey of recommendation techniques based on offline data processing,” Concurrency and Computation: Practice and Experience, 2014. View at Publisher · View at Google Scholar
  • Marcel Bouchard, Jennifer Haegele, and Henry Hexmoor, “Crowd dynamics of behavioural intention: train station and museum case studies,” Connection Science, pp. 1–24, 2014. View at Publisher · View at Google Scholar
  • David Geiger, and Martin Schader, “Personalized Task Recommendation in Crowdsourcing Information Systems – Current State of the Art,” Decision Support Systems, 2014. View at Publisher · View at Google Scholar
  • Josef Bauer, and Alexandros Nanopoulos, “Recommender Systems based on Quantitative Implicit Customer Feedback,” Decision Support Systems, 2014. View at Publisher · View at Google Scholar
  • Ahmed Hosny, and Vijay K. Sood, “Transformer differential protection with phase angle difference based inrush restraint,” Electric Power Systems Research, 2014. View at Publisher · View at Google Scholar
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  • Shuiguang Deng, Longtao Huang, and Guandong Xu, “Social Network-based Service Recommendation with Trust Enhancement,” Expert Systems with Applications, 2014. View at Publisher · View at Google Scholar
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