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An improved recommendation algorithm via weakening indirect linkage effect

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Chinese Physics B 2015年第7期24卷 606-611页

作者：陈光邱天沈小泉 School of Information Engineering Nanchang Hangkong University

We propose an indirect-link-weakened mass diffusion method（IMD）, by considering the indirect linkage and the source object heterogeneity effect in the mass diffusion（MD） recommendation method. Experimental results on the MovieLens, Netflix, and RYM datasets show that, the IMD method greatly improves both the recommendation accuracy and diversity, compared with a heterogeneity-weakened MD method（HMD）, which only considers the source object heterogeneity. Moreover, the recommendation accuracy of the cold objects is also better elevated in the IMD than the HMD method. It suggests that eliminating the redundancy induced by the indirect linkages could have a prominent effect on the recommendation efficiency in the MD method.

关键词： bipartite network mass diffusion recommender system indirect linkage effect

Deciphering microeukaryotic–bacterial co-occurrence networks in coastal aquaculture ponds

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Marine Life Science & Technology 2023年第1期5卷 44-55页

作者： Xiafei Zheng Kui Xu Jonathan Naoum Yingli Lian Bo Wu Zhili He Qingyun Yan Ninghai Institute of Mariculture Breeding and Seed Industry Zhejiang Wanli UniversityNingbo315100China Environmental Microbiomics Research Center School of Environmental Science and EngineeringState Key Laboratory for BiocontrolSouthern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Sun Yat-Sen UniversityGuangzhou510006China Hubei Key Laboratory of Edible Wild Plants Conservation and Utilization Hubei Engineering Research Center of Special Wild Vegetables Breeding and Comprehensive Utilization TechnologyCollege of Life SciencesHubei Normal UniversityHuangshi435002China Department of Biological Sciences Ecotoxicology of Aquatic Microorganisms LaboratoryGRIL-EcotoQ-TOXENUniversitéDu QuébecÀMontréalSuccursale Centre-VilleMontrealQCCanada Animal Husbandry and Fisheries Research Center of Guangdong Haid Group CO. Ltd.Key Laboratory of Microecological Resources and Utilization in Breeding IndustryMinistry of Agriculture and Rural AffairsGuangzhou510006China

Microeukaryotes and bacteria are key drivers of primary productivity and nutrient cycling in aquaculture *** their diversity and composition have been widely investigated in aquaculture systems,the co-occurrence bipartite network between microeukaryotes and bacteria remains poorly *** study used the bipartite network analysis of high-throughput sequencing datasets to detect the co-occurrence relationships between microeukaryotes and bacteria in water and sediment from coastal aquaculture *** and fungi were dominant phyla in the microeukaryotic–bacterial bipartite networks in water and sediment,*** also had overrepresented links with bacteria in *** microeukaryotes and bacteria were classified as generalists,and tended to have symmetric positive and negative links with bacteria in both water and ***,some microeukaryotes with high density of links showed asymmetric links with bacteria in *** detection in the bipartite network indicated that four microeukaryotes and twelve uncultured bacteria might be potential keystone taxa among the module ***,the microeukaryotic–bacterial bipartite network in sediment harbored significantly more nestedness than that in *** loss of microeukaryotes and generalists will more likely lead to the collapse of positive co-occurrence relationships between microeukaryotes and bacteria in both water and *** study unveils the topology,dominant taxa,keystone species,and robustness in the microeukaryotic–bacterial bipartite networks in coastal aquaculture *** species herein can be applied for further management of ecological services,and such knowledge may also be very useful for the regulation of other eutrophic ecosystems.

关键词： Microeukaryote bipartite network Interactions Keystone taxa Nestedness

Detecting Communities by Revised Max-flow Method in networks

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Communications in Theoretical Physics 2013年第8期60卷 258-262页

作者：刘传建朱志强吴建良 School of Mathematics Shandong University

A ubiquitous phenomenon in networks is the presence of communities within which the network connections are dense and between which they are *** paper proposes a max-flow algorithm in bipartite networks to detect communities in general ***,we construct a bipartite network in accordance with a general network and derive a revised max-flow problem in order to uncover the community *** we present a local heuristic algorithm to find the optimal solution of the revised max-flow *** method is applied to a variety of real-world and artificial complex networks,and the partition results confirm its effectiveness and accuracy.

关键词： community structure max-flow bipartite network

ECOLOGICAL networkS IN AGROECOSYSTEMS: APPROACHES AND APPLICATIONS

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Frontiers of Agricultural Science and Engineering 2022年第4期9卷 523-535页

作者： Ying GONG Langqin YU Lei ZHAO Beijing Key Laboratory of Biodiversity and Organic Farming College of Resources and Environmental SciencesChina Agricultural UniversityBeijing 100193China

Complex network theory has been increasingly used in various research areas,including *** paper summarizes the basic concepts and approaches commonly used in complex network theory,and then reviews recent studies on the applications in agroecosystems of three types of common ecological networks,i.e.,food webs,pollination networks and microbial co-occurrence *** general,agricultural intensification is considered to be a key driver of the change of *** causes the simplification of landscape,leads to the loss of biocontrol through cascading effect in food webs,and also reduces the complexity and connectance of soil food *** pollination networks,agricultural intensification impaired the robustness by reducing specialization and enhancing *** microbial co-occurrence networks with high connectance and low modularity generally corresponded to high efficiency in utilization of nutrients,and high resistance to crop *** review aims to show the readers the advances of ecological networks in agroecosystems and inspire the researchers to conduct their studies in a new network perspective.

关键词： bipartite network co-occurrence network food web network theory

Personalized Recommendation Algorithm Based on Rating System and User Interest Association network

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Journal of Applied Mathematics and Physics 2022年第12期10卷 3496-3509页

作者： Jiaquan Huang Zhen Jia College of Science Guilin University of Technology Guilin China

In most available recommendation algorithms, especially for rating systems, almost all the high rating information is utilized on the recommender system without using any low-rating information, which may include more user information and lead to the accuracy of recommender system being reduced. The paper proposes a algorithm of personalized recommendation (UNP algorithm) for rating system to fully explore the similarity of interests among users in utilizing all the information of rating data. In UNP algorithm, the similarity information of users is used to construct a user interest association network, and a recommendation list is established for the target user with combining the user interest association network information and the idea of collaborative filtering. Finally, the UNP algorithm is compared with several typical recommendation algorithms (CF algorithm, NBI algorithm and GRM algorithm), and the experimental results on Movielens and Netflix datasets show that the UNP algorithm has higher recommendation accuracy.

关键词： Recommender Systems Association network Similarity bipartite network Collaborative Filtering

Research of E-commerce Resource Allocation Method Based on Clustering

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Research of E-commerce Resource Allocation Method Based on C...

第三十九届中国控制会议

作者： Dongming Chen Panpan Du Qiang Zhang Dongqi Wang Xinyu Huang Software College Northeastern University

This paper focuses on the research of diversified e-commerce activities in e-commerce platform, mapping various business activities into the framework of resource allocation. When a certain number of users access the platform concurrently, the system allocates resources. This paper abandons the traditional simple filtering mode to analyze the historical data of ecommerce platform, abstracts the user commodity binary network and divides the user communities according to the attribute information of users and commodities and the purchase logs of users. By analyzing the community of users, we can allocate resources reasonably. In the binary network of users and goods, there are still many problems in user based clustering. For example, the sparseness of user attribute information, the proportion of intersection between users’ purchasing goods is too small and so on. According to the characteristics of data and the existing problems, this paper selects the SimRank algorithm and improves it. In this paper, a combined similarity index based on user attributes and network structure is proposed to improve the accuracy of user clustering, and a reasonable scheme of resource allocation is proposed by using the community division of users,which increases the accuracy of user clustering, achieves the expected design goals, and improves work efficiency.

关键词： Electronic commerce bipartite network SimRank resource allocation

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