Conference Information

FIRE 2023: Forum for Information Retrieval Evaluation

Please Login to view website of conference
Free account: view official websites, track deadlines, and get email reminders.
Register Login
Embed deadline badge
FIRE
Get this via API
Search and ranking lists need no credentials at all; full detail for this page needs a free API key. See the developer guide.
Submission Date:
2023-09-14
Notification Date:
2023-10-30
Conference Date:
2023-12-15
Location:
Panjim, India
Years:
15
Viewed: 7468   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

47.2 / 100
Ranked #2,216 of 5,682 conferences · Top 39%

#126 of 337 in Data Mining & Databases

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
75
Community attention (10%)
10
Public record completeness (15%)
25

Inputs used: Editions on record: 15 · Researchers who opened this page in the past 24 months: 3

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-16

Call For Papers

FIRE 2023 (Forum for Information Retrieval Evaluation) is an academic conference held in Panjim, India on 2023-12-15. The paper submission deadline is 2023-09-14. Acceptance notifications are sent on 2023-10-30.

The 15th meeting of the Forum for Information Retrieval Evaluation 2023 will be held at Goa University, Panjim, India. It will be an in-person conference. We are seeking submissions of high-quality and original papers. Submissions will be reviewed by experts on the basis of the originality of the work, the validity of the results, chosen methodology, writing quality, and the overall contribution to the field of IR/NLP. Authors are also encouraged to describe work in progress and late-breaking research results. Topics of interest include, but are not limited to Search and Ranking: Research on core algorithmic topics in IR: Queries and query analysis (e.g., Query understanding, query reformulation, query representation, etc.) Retrieval models and ranking (e.g., Cross lingual IR with a particular focus on Indian languages, ranking algorithms, language models, retrieval algorithms, learning to rank, etc.) Efficiency and scalability (e.g., distributed search, search engine architecture, indexing, crawling, etc.) Domain Specific: Research on domain specific IR: Applications in Social Media (e.g., Hate speech recognition, social network in search, etc.) Applications in Finance (e.g., Stock market prediction, other applications in finance) Applications in Legal (e.g., Patent discovery, verdict summarization, other applications in law) Applications in Health (e.g., Biomedical IR, medicine, genomics, other applications in health) Other applications and domains Recommendation Systems: Research on Recommendation systems, content representation, and content analysis: Recommendation algorithms (e.g., Content based filtering, collaborative filtering, etc.) Document representation and analysis (e.g., Summarization, text representation, sentiment analysis, etc.) Knowledge acquisition (e.g., Information extraction, event extraction, etc.) Multimodal and Crossmodal IR/Recsys model Visual Question Answering Image search/recommendation Multimodal document summarization Bridging the gap between AI and IR: Supervised/Weakly supervised deep neural networks Word Embedding Methodologies and its applications Question answering Conversational systems Machine Translation Evaluation: Research on evaluation of IR systems: User centric evaluation (e.g., User experience, user engagement, etc.) System centric evaluation (e.g., Evaluation metrics) Explainability, Fairness, and Trust of IR/Recsys models Explainable models for ranking, text classification/clustering, summarization, etc. User studies for explainable AI (XAI) applied to IR/Recsys Issues related to fairness and trustworthiness of IR/Recsys models
Last updated by Dou Sun on

Related Conferences

Related Journals

CCFFull NameImpact FactorPublisherISSN
International Journal of Multimedia Information Retrieval2.9Springer2192-6611
BPerformance Evaluation1.0Elsevier0166-5316
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203

Comments 0

No comments yet.

Please Login to post a comment