With the development of information technology, online learning has gradually become an indispensable way of knowledge acquisition. However, with the increasing amount of data information, it is increasingly difficult...With the development of information technology, online learning has gradually become an indispensable way of knowledge acquisition. However, with the increasing amount of data information, it is increasingly difficult for people to find appropriate learning materials from a large number of educational resources. The recommender system has been widely used in various Internet applications due to its high efficiency in filtering information, helping users to quickly find personalized resources from thousands of information, thereby alleviating the problem of information overload. In addition, due to its great use value, many new researches have been proposed in the field of recommender systems in recent years, but there are not many works on online course recommendation at present. Therefore, this paper aims to sort out the existing cutting-edge recommendation algorithms and the work related to online course recommendation, so as to provide a comprehensive overview of the online course recommender system. Specifically, we will first introduce the main technologies and representative work used in the online course recommender system, explain the advantages and disadvantages of various technologies, and finally discuss the future research direction of the online course recommender system.展开更多
To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user...To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.展开更多
Recent years have witnessed the booming of online social network and social media platforms,which leads to a state of information explosion.Though extensive efforts have been made by publishers to struggle for the lim...Recent years have witnessed the booming of online social network and social media platforms,which leads to a state of information explosion.Though extensive efforts have been made by publishers to struggle for the limited attention of audiences,still,only a few of information items will be received and digested.Therefore,for simulating the information propagation process,competition among propagating items should be considered,which has been largely ignored by prior works on propagation modeling.One possible reason may be that,it is almost impossible to identify the influence of propagation background from real diffusion data.To that end,in this paper,we design a comprehensive framework to simulate the propagation process with the characteristics of user behaviors and network topology.Specifically,we propose a propagation background simulating(PBS)algorithm to simulate the propagation background by using users′behavior dynamics and out-degree.Along this line,an ICPB(independent cascade with propagation background)model is adapted to relieve the impact of propagation background by using users′in-degree.Extensive experiments on kinds of synthetic and real networks have demonstrated the effectiveness of our methods.展开更多
文摘With the development of information technology, online learning has gradually become an indispensable way of knowledge acquisition. However, with the increasing amount of data information, it is increasingly difficult for people to find appropriate learning materials from a large number of educational resources. The recommender system has been widely used in various Internet applications due to its high efficiency in filtering information, helping users to quickly find personalized resources from thousands of information, thereby alleviating the problem of information overload. In addition, due to its great use value, many new researches have been proposed in the field of recommender systems in recent years, but there are not many works on online course recommendation at present. Therefore, this paper aims to sort out the existing cutting-edge recommendation algorithms and the work related to online course recommendation, so as to provide a comprehensive overview of the online course recommender system. Specifically, we will first introduce the main technologies and representative work used in the online course recommender system, explain the advantages and disadvantages of various technologies, and finally discuss the future research direction of the online course recommender system.
基金Supported by the National Natural Science Foundation of China(51375049)National Defense Basic Scientific Research(A222011A222013)
文摘To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.
基金This work was supported by National Natural Science Foundation of China(Nos.91546110,61703386,61727809 and U1605251).
文摘Recent years have witnessed the booming of online social network and social media platforms,which leads to a state of information explosion.Though extensive efforts have been made by publishers to struggle for the limited attention of audiences,still,only a few of information items will be received and digested.Therefore,for simulating the information propagation process,competition among propagating items should be considered,which has been largely ignored by prior works on propagation modeling.One possible reason may be that,it is almost impossible to identify the influence of propagation background from real diffusion data.To that end,in this paper,we design a comprehensive framework to simulate the propagation process with the characteristics of user behaviors and network topology.Specifically,we propose a propagation background simulating(PBS)algorithm to simulate the propagation background by using users′behavior dynamics and out-degree.Along this line,an ICPB(independent cascade with propagation background)model is adapted to relieve the impact of propagation background by using users′in-degree.Extensive experiments on kinds of synthetic and real networks have demonstrated the effectiveness of our methods.
