Knowledge Graph summarization for anomaly/error detection & completion (WebConf '20)
Summarization of static graphs using the Minimum Description Length principle
Slides and code for the Morgan Claypool book on "Individual and Collective Graph Mining: Principles, Algorithms and Applications"
Personalized knowledge graph summarization based on historical queries
This repository contains various models for text summarization tasks. Each model has a separate directory containing the implementation code, pretrained weights, and a Jupyter notebook for testing the model on sample input texts. Feel free to use these models for your own text summarization tasks or to experiment with them further.
Framework for latent network summarization: bridging network embedding and summarization
scaling RGCN training with graph summaries
This repo shows research paper upon which I worked during my summer research intern - 2022.
Unifying MoSSo with Mags-DM principles to achieve state-of-the-art compression and efficiency on fully dynamic graph streams. Developed as part of a Master's Thesis at NTNU.
The Graph Summarizer project is a command line project focusing on on simplifying complex graphs into short summaries while maintaining crucial information. Its goal is to help in easier visualization and analysis of graph data, increasing understanding and help people make smarter decisions.
Use LLM to describe a difference graph between versions of a compositional document (DOT graph).
To associate your repository with the graph-summarization topic, visit your repo's landing page and select "manage topics."