{"id":20377570,"url":"https://github.com/reshalfahsi/web-traffic-prediction","last_synced_at":"2026-06-09T05:02:02.821Z","repository":{"id":189493606,"uuid":"677003482","full_name":"reshalfahsi/web-traffic-prediction","owner":"reshalfahsi","description":"Web Traffic Prediction via Temporal Graph Neural Network","archived":false,"fork":false,"pushed_at":"2024-01-11T00:45:18.000Z","size":364,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-05-18T14:48:53.637Z","etag":null,"topics":["graph-neural-networks","pytorch-geometric-temporal","pytorch-lightning","temporal-data","temporal-graph-networks","web-traffic-forecasting"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/reshalfahsi.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-08-10T14:07:32.000Z","updated_at":"2024-11-06T06:26:12.000Z","dependencies_parsed_at":"2024-01-11T01:57:40.762Z","dependency_job_id":null,"html_url":"https://github.com/reshalfahsi/web-traffic-prediction","commit_stats":null,"previous_names":["reshalfahsi/web-traffic-prediction"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/reshalfahsi/web-traffic-prediction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/reshalfahsi%2Fweb-traffic-prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/reshalfahsi%2Fweb-traffic-prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/reshalfahsi%2Fweb-traffic-prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/reshalfahsi%2Fweb-traffic-prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/reshalfahsi","download_url":"https://codeload.github.com/reshalfahsi/web-traffic-prediction/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/reshalfahsi%2Fweb-traffic-prediction/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34092262,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-09T02:00:06.510Z","response_time":63,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["graph-neural-networks","pytorch-geometric-temporal","pytorch-lightning","temporal-data","temporal-graph-networks","web-traffic-forecasting"],"created_at":"2024-11-15T01:45:38.657Z","updated_at":"2026-06-09T05:02:02.805Z","avatar_url":"https://github.com/reshalfahsi.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Web Traffic Prediction via Temporal Graph Neural Network\n\n\n \u003cdiv align=\"center\"\u003e\n    \u003ca href=\"https://colab.research.google.com/github/reshalfahsi/web-traffic-prediction/blob/master/Web_Traffic_Prediction.ipynb\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"colab\"\u003e\u003c/a\u003e\n    \u003cbr /\u003e\n \u003c/div\u003e\n\n\nTemporal Graph Neural Network or Temporal GNN is one of the variants of the GNN which handles the spatio-temporal data. The term \"spatio-\" refers to the nature of the graph that is closely related to the spatial relationship that exists in the image data (recall that an image is basically a graph), and the term \"temporal\" here indicates the data may be progressively changing in a sequence of time. In this project, the [Chebysev GCNN+LSTM](https://arxiv.org/pdf/1612.07659.pdf) module and the Wiki Maths dataset are leveraged, which are provided by [PyTorch Geometric Temporal](https://github.com/benedekrozemberczki/pytorch_geometric_temporal). The complete Temporal GNN model contains the Chebysev GCNN+LSTM module, followed by a fully connected layer. Here, the model is trained to predict the daily user visits to Wikipedia's vital mathematics articles (represented by nodes/vertices). The graph's characteristic in the dataset is non-heterogenous and static. The details of the dataset can be seen [here](https://pytorch-geometric-temporal.readthedocs.io/en/latest/modules/dataset.html#torch_geometric_temporal.dataset.wikimath.WikiMathsDatasetLoader). \n\n\n## Experiment\n\n\nTo try out the experiment, the [Google Colab notebook](https://github.com/reshalfahsi/web-traffic-prediction/blob/master/Web_Traffic_Prediction.ipynb) is provided.\n\n\n## Result\n\n## Quantitative Result\n\nThe quantitative performance of the model is given in the table below.\n\nMetrics | Score |\n------------ | ------------- |\nLoss | 0.452 |\nMAPE | 4.110 |\nMAE | 0.438 |\nMSE | 0.519 |\n\n\n\n## Evaluation Metric Curve\n\n\u003cp align=\"center\"\u003e \u003cimg src=\"https://github.com/reshalfahsi/web-traffic-prediction/blob/master/assets/loss_curve.png\" alt=\"loss_curve\" \u003e \u003cbr /\u003e Loss curve of the training and validation of the Temporal GNN model. \u003c/p\u003e\n\n\u003cp align=\"center\"\u003e \u003cimg src=\"https://github.com/reshalfahsi/web-traffic-prediction/blob/master/assets/mape_curve.png\" alt=\"mape_curve\" \u003e \u003cbr /\u003e MAPE curve of the training and validation of the Temporal GNN model. \u003c/p\u003e\n\n\u003cp align=\"center\"\u003e \u003cimg src=\"https://github.com/reshalfahsi/web-traffic-prediction/blob/master/assets/mae_curve.png\" alt=\"mae_curve\" \u003e \u003cbr /\u003e MAE curve of the training and validation of the Temporal GNN model. \u003c/p\u003e\n\n\u003cp align=\"center\"\u003e \u003cimg src=\"https://github.com/reshalfahsi/web-traffic-prediction/blob/master/assets/mse_curve.png\" alt=\"mse_curve\" \u003e \u003cbr /\u003e MSE curve of the training and validation of the Temporal GNN model. \u003c/p\u003e\n\n\n## Qualitative Result\n\nThe figure below shows the qualitative result of the model.\n\n\u003cp align=\"center\"\u003e \u003cimg src=\"https://github.com/reshalfahsi/web-traffic-prediction/blob/master/assets/qualitative_result.png\" alt=\"qualitative_result\" \u003e \u003cbr /\u003e The visitor prediction at one of the vital mathematics articles on Wikipedia. \u003c/p\u003e\n\n\n## Credit\n\n- [Structured Sequence Modeling with Graph Convolutional Recurrent Networks](https://arxiv.org/pdf/1612.07659.pdf)\n- [PyTorch Geometric Temporal](https://github.com/benedekrozemberczki/pytorch_geometric_temporal)\n- [PyTorch Lightning](https://lightning.ai/docs/pytorch/latest/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freshalfahsi%2Fweb-traffic-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Freshalfahsi%2Fweb-traffic-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freshalfahsi%2Fweb-traffic-prediction/lists"}