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Collaborative Filtering with Preventing Fake Ratings

Dr. A. Srinivasa Rao, B. Bhagyalakshmi, Ab. Sirajunnisa | Md. Ashraf | E. Harika | Ch. Gangadhar
2018 International Journal of Trend in Scientific Research and Development  
In this paper, we increase a set of matrix factorization (MF) a nearest-neighbor (NN)-based recommended systems (RSs) that explore user social network and group association information for social voting  ...  During experiments with actual social voting traces, we express that social network and group association information can drastically progress the popularity-based voting advice, and social network in  ...  In this paper, we increase a set of matrix factorization (MF) and based recommended systems (RSs) that explore user social network and group association information for social voting recommendation.  ... 
doi:10.31142/ijtsrd11334 fatcat:hdapuiilrngxbn5fsbgah26x5i

Introduction to IT Enabled Collaboration in Developing Countries Minitrack

Xusen Cheng, Xiangbin Yan, Deepinder Bajwa
2015 2015 48th Hawaii International Conference on System Sciences  
Recommendation system is important for scientific collaboration. In their study, they have focused on scientific collaborator recommendation system in heterogeneous bibliographic networks.  ...  The second paper is "Scientific Collaborator Recommendation in Heterogeneous Bibliographic Networks" by Chen Yang, Jianshan Sun, Jian Ma, Shanshan Zhang, Gang Wang, Zhongsheng Hua.  ... 
doi:10.1109/hicss.2015.71 dblp:conf/hicss/ChengYB15 fatcat:addobobhfzgepgmfp6gbldaoke

Stepping beyond your comfort zone: Diffusion-based network analytics for knowledge trajectory recommendation [article]

Yi Zhang, Mengjia Wu, Jie Lu
2022 arXiv   pre-print
Hence, in this study, we present a method of diffusion-based network analytics for knowledge trajectory recommendation.  ...  The method begins by constructing a heterogeneous bibliometric network consisting of a co-topic layer and a co-authorship layer.  ...  As such, this paper proposes a novel method for analysing heterogeneous bibliometric networks and recommending knowledge trajectories to target researchers.  ... 
arXiv:2205.15504v1 fatcat:buo4olwjhfg4licchtakx6bvxq

Graph Embedding for Scholar Recommendation in Academic Social Networks

Chengzhe Yuan, Yi He, Ronghua Lin, Yong Tang
2021 Frontiers in Physics  
Different from friend recommendation in conventional social networks, scholar recommendation in ASNs usually involves different academic entities (e.g., scholars, scientific publications, and status updates  ...  The academic social networks (ASNs) play an important role in promoting scientific collaboration and innovation in academic society.  ...  A multilevel profile-based expert finding method for expert recommendation in online scientific communities is proposed in [25].  ... 
doi:10.3389/fphy.2021.768006 fatcat:qjmv3eyvmncktdqoid5vhldke4

Diffusing science through social networks: The case of breastfeeding communication on Twitter

Sara Moukarzel, Martin Rehm, Miguel del Fresno, Alan J. Daly, Sergi Lozano
2020 PLoS ONE  
In response to this call, we gathered data from Twitter for one month from major breastfeeding hashtags resulting in an interconnected social network (n = 3,798 users).  ...  These rates may be influenced by limited diffusion of evidence-based research and guidelines from the scientific community (SC).  ...  Influencers from the scientific community had less heterogenous relations than companies Perhaps due to brand competition and the nature of for-profit businesses, company networks were the most heterogenous  ... 
doi:10.1371/journal.pone.0237471 pmid:32790712 fatcat:yizk6nhvpveprjk5g7uuj7mdrm

Recommendation system based on heterogeneous feature: A survey

Hui Wang, ZiChun Le, Xuan Gong
2020 IEEE Access  
[12] It can differentiate tie strengths by considering heterogeneous strengths of social relations. It is unsuitable for dynamic network recommendation.  ...  a whole: Outfit Compatibility Learning based on Node-wise Graph Neural Networks [11] H.Wang: Recommendation system based on heterogeneous features: A Survey VOLUME XX, 2020 13 social networks and mobile  ... 
doi:10.1109/access.2020.3024154 fatcat:clxk77bcr5hdjd3hnxxi6wzlr4

An Overview on Evaluating and Predicting Scholarly Article Impact [article]

Xiaomei Bai, Hui Liu, Fuli Zhang, Zhaolong Ning, Xiangjie Kong, Ivan Lee, Feng Xia
2020 arXiv   pre-print
It is also used for addressing various needs in the academic and scientific arena, such as recruitment decisions, promotions, and funding allocations.  ...  Some core methods and recent progress are presented to outline how article impact metrics and prediction have evolved to consider integrating multiple networks.  ...  For example, Tweets can predict whether an article can be cited frequently when an article was published for 3 days [60] . Based on a heterogeneous scholarly network, Mohan et al.  ... 
arXiv:2008.03867v1 fatcat:esj4z5dsobbjrkuktyw3nzqghq

An Overview on Evaluating and Predicting Scholarly Article Impact

Xiaomei Bai, Hui Liu, Fuli Zhang, Zhaolong Ning, Xiangjie Kong, Ivan Lee, Feng Xia
2017 Information  
Some core methods and recent progress are presented to outline how article impact metrics and prediction have evolved to consider integrating multiple networks.  ...  It is also used for addressing various needs in the academic and scientific arena, such as recruitment decisions, promotions, and funding allocations.  ...  For example, Tweets can predict whether an article can be cited frequently when an article was published for 3 days [60] . Based on a heterogeneous scholarly network, Mohan et al.  ... 
doi:10.3390/info8030073 fatcat:qtlxuy2jengmtoo6kbp2shzjgy

Survey on entity linking for domain specific with heterogeneous information networks

S. Mythrei, S. Singaravelan
2019 Informatologia  
Heterogeneous information networks (HIN) comprises multiple-type interlinked objects with various types of relationship which are becoming increasingly most popular named bibliographic networks, social  ...  Knowledgebase (KB) is used to optimize the information collection, organization and for retrieval of information.  ...  This research proposed a Novel Heterogeneous network embedding based method for Recommendation which is known as HE-Rec.  ... 
doi:10.32914/i.52.3-4.5 fatcat:zd2ypopvpjfqnd3xw4tg57uuh4

Recommendation System based on Semantic Scholar Mining and Topic modeling: A behavioral analysis of researchers from six conferences [article]

Hamed Jelodar, Yongli Wang, Mahdi Rabbani, Ru-xin Zhao, Seyedvalyallah Ayobi, Peng Hu, Isma Masood
2018 arXiv   pre-print
Recommendation Systems in computer science are of very practical use these days in various aspects of the Internet portals, such as social networks, and library websites.  ...  Recently, researchers have proposed many approaches based on Recommendation Systems and LDA.  ...  -Group recommendation, Group activities are essential components for online users in social networks.  ... 
arXiv:1812.08304v1 fatcat:ql264icqmnamzbyz45fweujuxi

Academic Influence Aware and Multidimensional Network Analysis for Research Collaboration Navigation Based on Scholarly Big Data

Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Runhe Huang, Qun Jin
2018 IEEE Transactions on Emerging Topics in Computing  
The widespread adoption of social computing paradigm has made it easier for researchers to join collaborative research activities, and share the academic data more extensively than ever before across the  ...  In this study, we focus on the academic influence aware and multidimensional network analysis based on the integration of multi-source scholarly big data.  ...  [28] constructed a cluster-based citation recommendation framework, to predict query-related ciations based on relations of clustered interest groups within heterogeneous bibliographic networks.  ... 
doi:10.1109/tetc.2018.2860051 fatcat:4zujhixpzfcoxertjbvwy3f6ba

Expert recommendation based on social drivers, social network analysis, and semantic data representation

Maryam Fazel-Zarandi, Hugh J. Devlin, Yun Huang, Noshir Contractor
2011 Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems - HetRec '11  
Knowledge networks and recommender systems are especially important for expert finding within organizations and scientific communities.  ...  Useful recommendation of experts, however, is not an easy task for many reasons: It requires reasoning about multiple complex networks from heterogeneous sources (such as collaboration networks of individuals  ...  Social driver based recommenders integrate the level of expertise matching and the structure of social networks and make better recommendations.  ... 
doi:10.1145/2039320.2039326 fatcat:onoxqzzfdraj7pnfnjxd7sdt64

IEEE Access Special Section Editorial: Advanced Data Mining Methods for Social Computing

Yongqiang Zhao, Shirui Pan, Jia Wu, Huaiyu Wan, Huizhi Liang, Haishuai Wang, Huawei Shen
2020 IEEE Access  
Various kinds of social networks develop explosively, such as online social networks, scientific cooperation networks, athlete networks, airport passage networks, and so on.  ...  The second group, with ten articles, tackles social multimedia mining. The third group, with 12 articles, addresses machine learning for social data.  ... 
doi:10.1109/access.2020.3043060 fatcat:qbqk5f4ojvadlazhk2mc343sra

A Survey of Heterogeneous Information Network Analysis [article]

Chuan Shi, Yitong Li, Jiawei Zhang, Yizhou Sun, Philip S. Yu
2015 arXiv   pre-print
for data mining.  ...  In this paper, we provide a survey of heterogeneous information network analysis.  ...  Similarly, Wu et al. [136] exploit graph summarization and content-based clustering for media recommendation with the interest group information.  ... 
arXiv:1511.04854v1 fatcat:n2k3sulq3fbq3e34lrfrv3uoou

An Efficient Recommendation Algorithm Based on Heterogeneous Information Network

Ying Yin, Wanning Zheng
2021 Complexity  
At present, a large number of recommendation algorithms based on heterogeneous information networks have been proposed.  ...  Therefore, this paper proposes an efficient recommendation algorithm based on heterogeneous information network, which uses the characteristics of graph convolution neural network to automatically learn  ...  Luo et al. proposed a collaborative filtering social recommendation method based on heterogeneous relationships [7] . Recently, Shi et al.  ... 
doi:10.1155/2021/6689323 doaj:8d58f081cf154dfaaf6db7ed11cb0736 fatcat:57o6k5ehirexrdmwaedznkquxa
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