Social networks reflect the complex society constituted between people and can be simply described as a collection composed of individuals and organizations as subjects and the connections between these subjects. The connections in social networks can be the embodiment of real social relationships in real society, such as friendships, colleague relationships, family relationships, etc., or virtual relationships generated by interactions in the network, such as fan relationships, following relationships, sharing relationships, fun relationships, etc. Social network is a typical self-media network, where users publish, share and communicate information and are both producers and consumers of information.In order to analyze social networks effectively, a common approach is to extract important features from the network, that is, to convert a large network into a smaller one, while the latter is an effective summary of the former and maintains the important features of the original network. In social networks, this approach can be implemented in two ways, one is to identify groups of users and represent the relationships between them, which is often referred to as community discovery.
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Dr. Xun Liang has worked in the fields of social networks and machine learning for more than 20 years, and led many large research and industrial projects. He has published more than 260 papers and 20 books.
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Social networks reflect the complex society constituted between people and can be simply described as a collection composed of individuals and organizations as subjects and the connections between these subjects. The connections in social networks can be the embodiment of real social relationships in real society, such as friendships, colleague relationships, family relationships, etc., or virtual relationships generated by interactions in the network, such as fan relationships, following relationships, sharing relationships, fun relationships, etc. Social network is a typical self-media network, where users publish, share and communicate information and are both producers and consumers of information.In order to analyze social networks effectively, a common approach is to extract important features from the network, that is, to convert a large network into a smaller one, while the latter is an effective summary of the former and maintains the important features of the original network. In social networks, this approach can be implemented in two ways, one is to identify groups of users and represent the relationships between them, which is often referred to as community discovery. 176 pp. Englisch. Bestandsnummer des Verkäufers 9786203869385
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Liang XunDr. Xun Liang has worked in the fields of social networks and machine learning for more than 20 years, and led many large research and industrial projects. He has published more than 260 papers and 20 books.Social networ. Bestandsnummer des Verkäufers 482183550
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Social networks reflect the complex society constituted between people and can be simply described as a collection composed of individuals and organizations as subjects and the connections between these subjects. The connections in social networks can be the embodiment of real social relationships in real society, such as friendships, colleague relationships, family relationships, etc., or virtual relationships generated by interactions in the network, such as fan relationships, following relationships, sharing relationships, fun relationships, etc. Social network is a typical self-media network, where users publish, share and communicate information and are both producers and consumers of information.In order to analyze social networks effectively, a common approach is to extract important features from the network, that is, to convert a large network into a smaller one, while the latter is an effective summary of the former and maintains the important features of the original network. In social networks, this approach can be implemented in two ways, one is to identify groups of users and represent the relationships between them, which is often referred to as community discovery.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 176 pp. Englisch. Bestandsnummer des Verkäufers 9786203869385
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Social networks reflect the complex society constituted between people and can be simply described as a collection composed of individuals and organizations as subjects and the connections between these subjects. The connections in social networks can be the embodiment of real social relationships in real society, such as friendships, colleague relationships, family relationships, etc., or virtual relationships generated by interactions in the network, such as fan relationships, following relationships, sharing relationships, fun relationships, etc. Social network is a typical self-media network, where users publish, share and communicate information and are both producers and consumers of information.In order to analyze social networks effectively, a common approach is to extract important features from the network, that is, to convert a large network into a smaller one, while the latter is an effective summary of the former and maintains the important features of the original network. In social networks, this approach can be implemented in two ways, one is to identify groups of users and represent the relationships between them, which is often referred to as community discovery. Bestandsnummer des Verkäufers 9786203869385
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Taschenbuch. Zustand: Neu. Social Computing: User Networks and Information Dissemination | Xun Liang (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203869385 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 120287350
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