CLLGJul 2, 2024

The Solution for The PST-KDD-2024 OAG-Challenge

arXiv:2407.12827v1h-index: 2
Originality Synthesis-oriented
AI Analysis

This is an incremental solution for a specific competition in academic paper tracing.

The paper tackled the KDD-2024 OAG-Challenge paper source tracing track by combining BERT and GCN methods to process paper fragments and integrate contextual relationships, achieving a competition score of 0.47691.

In this paper, we introduce the second-place solution in the KDD-2024 OAG-Challenge paper source tracing track. Our solution is mainly based on two methods, BERT and GCN, and combines the reasoning results of BERT and GCN in the final submission to achieve complementary performance. In the BERT solution, we focus on processing the fragments that appear in the references of the paper, and use a variety of operations to reduce the redundant interference in the fragments, so that the information received by BERT is more refined. In the GCN solution, we map information such as paper fragments, abstracts, and titles to a high-dimensional semantic space through an embedding model, and try to build edges between titles, abstracts, and fragments to integrate contextual relationships for judgment. In the end, our solution achieved a remarkable score of 0.47691 in the competition.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes