تقرير
DynamicGEM: A Library for Dynamic Graph Embedding Methods
| العنوان: | DynamicGEM: A Library for Dynamic Graph Embedding Methods |
|---|---|
| المؤلفون: | Goyal, Palash, Chhetri, Sujit Rokka, Mehrabi, Ninareh, Ferrara, Emilio, Canedo, Arquimedes |
| سنة النشر: | 2018 |
| المجموعة: | Computer Science Statistics |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Social and Information Networks, Statistics - Machine Learning |
| الوصف: | DynamicGEM is an open-source Python library for learning node representations of dynamic graphs. It consists of state-of-the-art algorithms for defining embeddings of nodes whose connections evolve over time. The library also contains the evaluation framework for four downstream tasks on the network: graph reconstruction, static and temporal link prediction, node classification, and temporal visualization. We have implemented various metrics to evaluate the state-of-the-art methods, and examples of evolving networks from various domains. We have easy-to-use functions to call and evaluate the methods and have extensive usage documentation. Furthermore, DynamicGEM provides a template to add new algorithms with ease to facilitate further research on the topic. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1811.10734 |
| رقم الأكسشن: | edsarx.1811.10734 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |