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

About the workshop

In the field of information retrieval (IR), harnessing knowledge from external knowledge bases, such as Knowledge Graphs and Wikipedia, has emerged as a promising avenue for improving the effectiveness and the interpretability of IR systems. These external knowledge bases offer valuable information that empowers IR models to make more accurate predictions. 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 Knowledge-Enhanced Information Retrieval workshop (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 PLMs, IR models and RecSys models but also to facilitate in-depth discussions concerning the same.

Call for Papers

This workshop holds a steadfast commitment to fostering collaboration among researchers engaged in the realm of knowledge integration for IR, RecSys and NLP. We invite submissions regarding different aspects of knowledge-enhanced information retrieval systems. Relevant topics include, but are not limited to:

Knowledge-enhanced information retrieval models.
Knowledge-enhanced approaches for query processing, including query parsing, query expansion, relevance feedback, and query reformulation.
Knowledge-enhanced recommendation models.
Knowledge-enhanced language models for retrieval.
Data augmentation for knowledge-enhanced information retrieval.
Knowledge retrieval from unstructured data and structured data.
Applications of knowledge-enhanced retrievals, such as dialogue systems, question answering, summarisation and other domain-specific applications.
Data collection for knowledge-enhanced information retrieval.
Evaluation methodologies for knowledge-enhanced retrieval.
The interpretability and analysis of knowledge-enhanced models for IR, including potential biases and ethical considerations.

We invite authors to submit papers written in English. Submissions may range in length from a minimum of 6 pages to a maximum of 12 pages; however, references and supplementary materials may exceed this page count without limitation. In order to facilitate a double-blind review process, authors must ensure that submissions are fully anonymized. Please note that we do not impose a specific anonymity period prior to submission.

The papers (.pdf format) should be submitted using the EasyChair submission system at https://easychair.org/conferences/?conf=keirecir2024. Authors should consult Springer’s authors’ guidelines and use their proceedings templates to prepare the submission. The Microsoft Word and LaTeX versions of the template can be found at https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines. Submissions to KEIR@ECIR2024 will be peer-reviewed on the basis of technical quality, relevance to workshop topics, originality, significance, clarity, etc.
We accept submissions of the following types:

Original work that is not published or submitted elsewhere.
Work that is submitted elsewhere and is still under review. In this case, the authors should make sure that you are not violating the submission guidelines and anonymity requirements of the other venue(s).
Work that has been rejected at ECIR 2024.

The proceedings of the KEIR workshop will be non-archival in nature. Extended versions of selected papers will be recommended for special issues of several SCI-indexed international journals. However, authors retain the right to submit their work to other peer-reviewed venues for further dissemination.