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Titlebook: Event Attendance Prediction in Social Networks; Xiaomei Zhang,Guohong Cao Book 2021 The Author(s), under exclusive license to Springer Nat

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Group IV materials (mainly SiC),of the proposed solutions and evaluate how different parameters affect the performances. In this chapter, we first discuss the data selection, the experiment setting, and then present the evaluation results on the effectiveness of individual attributes and the performance of the three classifiers.
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https://doi.org/10.1007/0-306-46940-5ng approach to solve it. Experimental results based on the collected dataset demonstrated that the proposed approach can predict event attendance with high accuracy. Finally, we point out future research directions.
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Event Attendance Prediction: Attributes,res analysis of past events with similar topics. Therefore, we first present a semantic analysis method to calculate the semantic similarity between events, and then explain the three sets of context-aware attributes in details, i.e., semantic attributes, temporal attributes, and spatial attributes.
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