FIRE 2023

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The 15th meeting of the Forum for Information Retrieval Evaluation (FIRE) 2023 will be held at Goa Business School, Goa University, Panjim, India. It will be an in-person conference. In its milestone fifteenth year, FIRE brings in the Doctoral Consortium (DC) to provide a unique opportunity for doctoral students to share their work with peers as well as with senior researchers and also further shape up their research and develop new ones under an extended mentorship program under the guidance of distinguished researchers from both academia and industry.

The goals of the symposium are to:

• provide the participants with an independent and constructive assessment of their current research and possible future research scopes;
• develop a supportive community of scholars and a spirit of collaborative research;
• provide a platform for the doctoral participants to share and discuss their ideas with distinguished researchers from their domain; and support the participants further with an individual mentorship session with a distinguished researcher.

Who should participate?

Students should consider participating in the Doctoral Consortium if they are at least twelve months away from completing their dissertation at the time of the event, but after having settled on a research area or thesis topic.

In the area of research which largely covers AI / ML, information science related, we do not have any fixed set of research areas for the DC. However, it would be desirable to have information retrieval as a paradigm in your research that can be in any domain like software engineering, machine translation or image processing, etc.

Submission

Submissions can be based on early ideas, or results (communicated elsewhere) for further feedback, or well-rounded study, results, and analysis, on approach to convert PhD work into a product, and the like.

The paper should be 4 pages long (including references) and may contain the following aspects:

• the problem to be solved in the research; a justification of why the problem is important; a summary of the previous research and related work has not yet solved that problem,
• the expected contributions of the research,
• how the student aims to evaluate and analyze the results; acceptable evidence of the results to the community,
• an outline and characterization of the results achieved so far, and
• the planned timeline for completion.

Students, whose submissions are accepted, will be invited to present a poster at the consortium. They will also need to give a short talk at the consortium.

Paper submission link: https://cmt3.research.microsoft.com/FIRE2023

Format

The submitted papers must follow ACM SIG's template available on https://www.acm.org/publications/taps/word-template-workflow. The only accepted format of submissions is PDF. Papers which do not conform to the requirements may get rejected without review. Please note that it is the responsibility of the authors to ensure that the PDF submission has been uploaded successfully (we suggest that you try downloading your paper again yourself, to check). Authors are invited to submit in any of the following tracks:

Paper Length: 4 page single column

The author names and affiliations of the PhD Student or supervisors should be included in the paper during submission. The first author of the paper should be the PhD Student.

Review Process

Submissions will be reviewed by members of the Doctoral Symposium Committee. Participants will be selected on the basis of their anticipated contribution to the Doctoral Consortium goals as well as the potential benefit to the participants. Among the criteria that will be considered in reviewing submissions are:

• the potential quality of the anticipated contributions
• the stage of the research;
• the diversity of backgrounds, research topics, and approaches.

An additional review would be done to assess if the participants are eligible for the PhD clinic, where potential research work can be reviewed and discussed individually by a distinguished researcher.

Consortium and PhD Clinic

Authors of submissions selected for participation will have the opportunity to present their work during the Doctoral Consortium and to have a camera-ready version of their papers published in a companion volume to the FIRE 2023 Conference Proceedings and the ACM Digital Library.

The presentation is expected to be delivered in person, unless this is impossible due to travel limitations (related to, e.g., health, visa, or COVID-19 prevention).

Selected participants will be also be eligible for the PhD clinic wherein they will be assigned to a distinguished researcher who will conduct an individual mentoring session with the participants. This session can be constructively used by the participants to discuss their ideas, get more insights and feedback and also directions for future work.

Important dates 

10th April 2023	DC Paper submission link will be available
22nd September 2023	Paper submission deadline
30th October 2023	Paper acceptance notification
11th November 2023	Camera ready copy submission deadline
15th-18th December 2023	In-person conference

Note: All submission deadlines are 11:59 PM AoE Time Zone (Anywhere on Earth).

Selected Papers

• Relative Relation Representation Aware Link Prediction in Heterogeneous Information Network - Debasis Maji, Krishanu Mondal, Debaditya Barman
• Image Classification with Quantum Self Attention Neural Networks - Harshdeep Singh, I-Chi Chen, Kavitha Yogaraj, Brian Quanz
• A Study on the Effect of 2-Approximate Shortest-Path Integration in Extracting Context-Sensitive Dense Structures - AJAHARUL HOQUE, Debaditya Barman, Paramartha Dutta, Subhrangsu Mandal
• Towards Semantic Role Labeling of Legal Documents for Improving NLP/IR Tasks in the Law Domain - Subinay Adhikary
• Drug Uniformity and Content Detection for Pharmaceutical Formulations: The Deep Learning Approach - Abhishek D Patel, Amit Thakkar
• Student Behavior Detection in the classroom based on Human-Object Interaction model - Dharmendrasinh G Rathod, Amit Thakkar
• Towards development of an effective AI-based system for relevant comment generation - Tripti Kumari, Ayan Das
• Abstractive Summarization of Scientific Documents: Models and Evaluation Techniques - Tohida Rehman, Prof. Samiran Chattopadhyay, Debarshi Kumar Sanyal
• A Keyphrase-Centric Search Engine for Scientific Papers - Avishek Lahiri, Debarshi Kumar Sanyal, Imon Mukherjee
• A Personal Knowledge Graph for Researchers - Prantika Chakraborty, Debarshi Kumar Sanyal

 

Contact

• Srijoni Majumdar
• Soumen Paul

If there are queries regarding the CFP, please contact s.majumdar@leeds.ac.uk and soumenpaul165@gmail.com