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Chapter and Conference Paper
Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph Embedding
Knowledge graph embedding (KGE) aims to map entities and relations of a knowledge graph (KG) into a low-dimensional and dense vector space via contrasting the positive and negative triples. In the training pro...
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Chapter and Conference Paper
Reinforcement Learning in Information Cascades Based on Dynamic User Behavior
This paper studies the Influence Maximization problem based on information cascading within a random graph, where the network structure is dynamically changing according to users’ uncertain behaviors. The Dis...
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Chapter and Conference Paper
The Application Research of AlphaGo Double Decision System in Network Bad Information Recognition
As the carrier of information transmission, the internet inevitably contains much bad information. In view of this phenomenon, with the purpose of identifying the bad information in the network, we combine exi...
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Chapter and Conference Paper
A Recommender System for Mobile Commerce Based on Relational Learning
Recommender systems are intelligent tools to extract useful information from a large collection of online data. They have been widely used in various fields, including the recommendation of music, movies, docu...
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Chapter and Conference Paper
A Virtual Informal Learning System for Cultural Heritage
Computer graphics and digital technologies have opened up a myriad of ways for both preservation and transfer of cultural heritage information. The digital storage systems, digital lab notebooks and virtual mu...