Call FOR papers 

Topics

IIR offers the opportunity to present and discuss both theoretical and empirical research. Relevant topics include, but are not restricted to:

• Search and Ranking. Research on core Information Retrieval (IR), including IR at scale, covering topics such as:

  • Theoretical models and foundations of IR and access;

  • Retrieval and ranking models, including diversity and aggregated search;

  • Web search, including link analysis, sponsored search, search advertising, adversarial search and spam, and vertical search;

  • Cross- and multi-lingual search;

  • Queries and query analysis;

• Recommendation. Research focusing on Information Filtering and Recommender Systems, covering topics such as:

  • Information Filtering and Recommendation, including Collaborative Filtering, Content-based Filtering, Hybrid Recommender Systems, Context-aware Recommendation;

  • Deep Learning in RecSys, Scalability and Efficiency, Evaluation Metrics and Methodologies, User Interfaces and Visualization;

  • Privacy, Security, and Ethics, Domain-specific Recommendations, Social and Trust-based Recommendations, Explainable and Interpretable Recommendations;

• Content Representation and Analysis. Research focusing on content representations and analysis, covering topics such as:

  • Document representation, including multimodal representation;

  • Content analysis and information extraction, including readability, sentiment analysis, and opinion mining;

  • Clustering, classification, summarization, and topic modelling;

• Artificial Intelligence, NLP, Semantics, and Dialog. Research bridging AI and IR, especially toward deep semantics — and dialog with intelligent agents, covering topics such as:

  • Question Answering;

  • Conversational systems, including spoken language interfaces, dialog management systems, and intelligent chat systems;

  • Semantics and knowledge graphs;

  • Deep learning for IR, embeddings, Large Language Models, and agents;

• Domain-Specific Applications. Research focusing on domain-specific challenges, covering topics such as:

  • Social search;

  • Search in structured data, including email and entity search;

  • Multimedia search;

  • Search and recommendation for Educational, Legal, Health – including genomics and bioinformatics – and academic domains;

  • Other domains such as digital libraries, enterprise, news, app, and archival search;

• Human Factors and Interfaces. Research into user-centric aspects of IR, including user interfaces, behavior modeling, privacy, and interactive systems, covering topics such as:

  • Mining and modelling search activity, including user and task models, click models, log analysis, behavioral analysis, and attention modelling;

  • Interactive and personalized search and recommendation;

  • Collaborative search, social tagging, and crowdsourcing;

  • Information privacy and security;

• Evaluation. Research that focuses on the measurement and evaluation of IR and Recommender Systems, covering topics such as:

  • User-centered evaluation methods, including measures of user experience and performance, user engagement, and search task design;

  • Test collections and evaluation metrics, including the development of new test collections;

  • Evaluation of novel information access tasks and systems such as multi-turn information access;

  • Statistical methods and reproducibility issues in information retrieval evaluation;

  • Efficiency and scalability;

• Future Directions. Research with theoretical or empirical contributions on new technical or social aspects of IR, especially in more speculative directions or with emerging technologies, covering topics such as:

  • Novel approaches to IR and RS;

  • Ethics, economics, and politics;

  • Applications of search and recommendation to social good;

  • IR and RS with new devices, including wearable computing, neuroinformatics, sensors, Internet-of-Things, vehicles;

We particularly encourage PhD students or Early-Stage Researchers to submit their research. We also welcome contributions from the industry and papers describing ongoing funded projects which may result useful to the IR community.

Authors are invited to submit one of the following types of contributions:

• Full papers (10 pages, plus unlimited pages for references);

• Short papers (5 pages, plus unlimited pages for references);

• Extended abstracts containing descriptions of ongoing projects or presenting already published results (up to 4 pages, plus unlimited pages for references). If presenting already published results the extended abstract should not be anonymous and contain a reference to the original published paper.

Submissions of research papers must be in English, single blind, in PDF format in the CEUR-WS single-column conference format available either at Overleaf CEUR-WS repository website or (for the offline version).

Submission will be peer-reviewed and single-blind. The authors of the accepted papers will have the possibility to decide whether the paper will appear or not in the CEUR Workshop Series Proceedings.

Submission will be through the submission system at the following link: TO BE ANNOUNCED

TO BE ANNOUNCED