Telecom package recommendation model based on convolutional neural network

Xiaoling Xia; Guanghui Zhao

doi:10.1117/12.2683672

26 June 2023 Telecom package recommendation model based on convolutional neural network

Xiaoling Xia, Guanghui Zhao

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 127210B (2023) https://doi.org/10.1117/12.2683672
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

In today's society, the demand for telecom packages is increasing and at the same time, there are many different types of telecom packages, so we need to recommend different types of telecom packages to different users so that each user can find the most suitable package for themselves among the many packages. We choose to build a click-through prediction model to model the interaction between user characteristics and telecom package characteristics. In this paper, we propose the FGCIN model, which generates new features by capturing important feature interactions through a convolutional neural network FGCNN, and then interacts the new features with the original features at the feature interaction layer through a compressed interaction network CIN for higher order features, followed by a deep neural network DNN for implicit feature interactions to finalize the output. In this paper we use the private dataset Telecom dataset and the public dataset Criteo for comparison experiments and ablation experiments, thus demonstrating the effectiveness and rationality of our proposed model FGCIN.

Citation Download Citation

Xiaoling Xia and Guanghui Zhao "Telecom package recommendation model based on convolutional neural network", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 127210B (26 June 2023); https://doi.org/10.1117/12.2683672

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