Retrieval and Sorting of Scientific Documents Based on Stacked Embedding and Hybrid Attention Model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AFJ9LD8EX" target="_blank" >RIV/00216208:11320/25:FJ9LD8EX - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205027088&doi=10.1109%2fIJCNN60899.2024.10650167&partnerID=40&md5=3e8135cb0ef64c463c11d5477335a0d4" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205027088&doi=10.1109%2fIJCNN60899.2024.10650167&partnerID=40&md5=3e8135cb0ef64c463c11d5477335a0d4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IJCNN60899.2024.10650167" target="_blank" >10.1109/IJCNN60899.2024.10650167</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Retrieval and Sorting of Scientific Documents Based on Stacked Embedding and Hybrid Attention Model

Popis výsledku v původním jazyce

Making full use of mathematical formulas and their contextual information is crucial for enhancing the performance of scientific literature retrieval models, where mathematical formulas serve as core elements. The existing methods inadequately use formula structure and contextual information in situations involving mathematical formulas, and ignore the part-of-speech features contained in the context. A two stage scientific document retrieval method, based on stacked embedding and hybrid attention fusion part-of-speech features, was proposed in this paper. Initially, MathML in documents is used to learn the structural and semantic information of mathematical formulas, facilitating scientific document retrieval focused on mathematical expression. Subsequently, the document context is extracted, the context's part-of-speech features are introduced into the model through stacked embeddings, and a hybrid attention mechanism is used to learn the dependency between part-of-speech and context, features are then generated to improve the rationality of retrieval result ranking. Experiments were performed on the NTCIR-12 dataset in which we expanded with Chinese literature. The mAP@10 is 0.865 and NDCG@10 is 0.863 respectively. © 2024 IEEE.

Název v anglickém jazyce

Retrieval and Sorting of Scientific Documents Based on Stacked Embedding and Hybrid Attention Model

Popis výsledku anglicky

Making full use of mathematical formulas and their contextual information is crucial for enhancing the performance of scientific literature retrieval models, where mathematical formulas serve as core elements. The existing methods inadequately use formula structure and contextual information in situations involving mathematical formulas, and ignore the part-of-speech features contained in the context. A two stage scientific document retrieval method, based on stacked embedding and hybrid attention fusion part-of-speech features, was proposed in this paper. Initially, MathML in documents is used to learn the structural and semantic information of mathematical formulas, facilitating scientific document retrieval focused on mathematical expression. Subsequently, the document context is extracted, the context's part-of-speech features are introduced into the model through stacked embeddings, and a hybrid attention mechanism is used to learn the dependency between part-of-speech and context, features are then generated to improve the rationality of retrieval result ranking. Experiments were performed on the NTCIR-12 dataset in which we expanded with Chinese literature. The mAP@10 is 0.865 and NDCG@10 is 0.863 respectively. © 2024 IEEE.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proc Int Jt Conf Neural Networks

ISBN

979-835035931-2

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

1-8

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

—

Místo konání akce

Yokohama

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—