Mar 11, 2022 · We formulate the problem of graph summarization as a subgraph classification task on the root vertex of the k -hop neighborhood. We adapt different GNN architectures, both based on the popular message-passing protocol and alternative approaches, to perform the structural graph summarization task.

Graph summarization finds smaller representations of graphs resulting in faster runtime of algorithms, reduced storage needs, and noise reduction. Summarization has applications in areas such as visualization, pattern mining, clustering and community detection, and more.

May 17, 2024 · This blog post provides an in-depth tutorial on implementing GraphRAG for query-focused summarization. It explains the process of building an entity knowledge graph, detecting communities, and generating final answers using Python.

Apr 7, 2020 · Automatic source code summarization is the task of generating natural language descriptions for source code. Automatic code summarization is a rapidly expanding research area, especially as the community has taken greater advantage of …

Jun 22, 2018 · Graph summarization is beneficial in a wide range of applications, such as visualization, interactive and exploratory analysis, approximate query processing, reducing the on-disk storage footprint, and graph processing in modern hardware.

To address this limitation and take full advantage of both code structure information and pre-trained models, in this paper, we propose GraphPLBART: a graph-augmented code summarization ap-proach based on the PLBART pre-trained model [13].

Mar 1, 2023 · In order to address the above-mentioned challenges, we propose a novel automated code summarization model named CLG-Trans in this work. This model uses the Byte Pair Encoding (BPE) algorithm and pointer-generator network to tackle the OOV problem.

Dec 14, 2016 · We first broach the motivation behind, and the challenges of, graph summarization. We then categorize summarization approaches by the type of graphs taken as input and further organize each category by core methodology. Finally, we discuss applications of summarization on real-world graphs and conclude by describing some open problems in the field.

Sep 12, 2020 · Source code summarization aims to automatically generate concise summaries of source code in natural language texts, in order to help developers better understand and maintain source code. Traditional work generates a source code summary by utilizing ...

In this article we will understand Graph based approach for text summarization (also known as Graph Reduction). It uses techniques to reducing graph size such as predicate-argument mapping and normalization.