KEIR @ ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval

被引：0

作者：

Meng, Zaiqiao ^{[1
]}

Liang, Shangsong ^{[2
]}

Xin, Xin ^{[3
]}

Moro, Gianluca ^{[4
]}

Kanoulas, Evangelos ^{[5
]}

Yilmaz, Emine ^{[6
]}

机构：

[1] Univ Glasgow, Glasgow, Lanark, Scotland

[2] MBZUAI, Abu Dhabi, U Arab Emirates

[3] Shandong Univ, Jinan, Peoples R China

[4] Univ Bologna, Bologna, Italy

[5] Univ Amsterdam, Amsterdam, Netherlands

[6] UCL, London, England

来源：

ADVANCES IN INFORMATION RETRIEVAL, ECIR 2024, PT V | 2024年 / 14612卷

关键词：

Information Retrieval; Knowledge Graph; Recommendation System; Large Language Models;

D O I：

10.1007/978-3-031-56069-9_53

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The infusion of external knowledge bases into IR models can provide enhanced ranking results and greater interpretability, offering substantial advancements in the field. The first workshop on Knowledge-Enhanced Information Retrieval (KEIR @ ECIR 2024) will serve as a platform to bring together researchers from academia and industry to explore and discuss various aspects of knowledge-enhanced information retrieval systems, such as models, techniques, data collection and evaluation. The workshop aims to not only deliberate upon the advantages and hurdles intrinsic to the development of knowledge-enhanced pretrained language models, IR models and recommendation models but also to facilitate in-depth discussions concerning the same.

引用

页码：398 / 402

页数：5

共 44 条

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