Experience the conference , from the comfort of your own home. CIKM 2022 is going hybrid.

Mohammad Al Hasan
General Chair
CIMK 2022

Program

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The CIKM 2022  program will host papers, posters, tutorials, workshops, and more that highlight  interesting problems being explored in the fields of Information and Knowledge Management.

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Monday, Oct 17
Tuesday, Oct 18
Wednesday, Oct 19
Thursday, Oct 20
Friday, Oct 21
Time
8:30 - 9 AM
EDT
Opening
9 - 10 AM
EDT
Keynote: Ling Liu (Georgia Institute of Technology) - "Ensemble Learning Methods for Dirty Data"
10:30 - 12:20 PM
EDT
Industry Day : E-commerce and Search
S1–A: Biomedical and Drug Informatics
S1–b: Transfer Learning
S1–c: Federated Learning
S1–d: Trajectories
S1–e: Multi-modal Data
S1–f: Advertising & E-commerce
S1–G: Personalization
2  - 3 PM
EDT
Industry day Keynote : Vanessa Murdock (Amazon Alexa Science) - "Customer Obsessed Science"
3:30 - 5:20 PM
EDT
Industry Day : Novel applications
S2–A: Privacy and Security
S2–b: Search and Evaluation
S2–c: Sequential Recommendation
S2–d: Time-Series Data
S2–e: poster/demo lightening
S2–f: Recommender Systems
S2–G: Network Embedding and Graph Recommendation
5:30 - 7 PM
EDT
Poster/Demo 1 + reception
Key
research papers
applied papers
tutorials
industry day talks
poster/demo lightening
PhD symposium
Time
9 - 10 AM
EDT
10:30 - 12:20 PM
EDT
S3-a: Innovative Applications
S3-b: Contrastive Learning
S3-c: Reinforcement Learning
S3-d: Collaborative Filtering
S3-e: Causal Learning
S3-f: Maps & Satellite Imagery Applications
S3-g: Social Good & Fairness
S3-h: Reinforcement Learning
2 - 3:30 PM
EDT
S4–A: Molecular Graphs & Chemsitry
S4–b: Link Prediction
S4–c: Knowledge Graphs and Entities
S4–d: Scalability and Efficiency
S4–e: Mining and Learning
S4–f: Recommender systems
S4–G: Self-Supervised Learning for Recommendation
S4–H: Deep Learning Interpretation for Image, NLP and DRL
4  - 5:30 PM
EDT
s5-a: Traffic Data
s5-b: Adversarial Learning
s5-c: Pre-training
s5-d: Graph Learning
s5-e: poster/demo lightening
s5-f: Knowledge Graphs & Knowledge Representations
s5-g: Self-Supervised Learning for Recommendation
s5-h: Deep Learning Interpretation for Image, NLP and DRL
5:30 - 7 PM
EDT
poster/demo 2 short/resource + demo + reception
Key
research papers
applied papers
tutorials
industry day talks
poster/demo lightening
PhD symposium
Time
9 - 10 AM
EDT
Keynote: Jaime Teevan (Microsoft) - "How Hybrid Work Will Make Work More Intelligent"
10:30 - 12:20 PM
EDT
S6-a: Explainablility and Interpretability
S6-b: Sentiment, Opinon, Dynamics and Spread
S6-c: Multi-label and Imbalance / CommonSense
S6-d: Conversation and Dialogue
S6-e PhD symposium
S6-f: Advertising & E-commerce
S6-g: Systems, Optimization & Security
S6-h: Data Applications & Social Networks
2 - 3:30 PM
EDT
S7–A: Algorithmic Biases
S7–b: Contrastive Learning
S7–c: Cross-Domain Recommendation
S7–d: Zero-shot and Few-shot Learning
S7–e PhD symposium
S7–f: Systems, Optimization & Security
S7–G: Mining of Real-world Hypergraphs: Patterns, Tools, and Generators
S7–H: Learning and Mining with Noisy Labels
4  - 5:30 PM
EDT
s8-a: Querying and Hashing
s8-b: Advertisements
s8-c: Contrastive Learning
s8-d:Click-through Rate Prediction
s8-e PhD symposium
s8-f: Recommender systems
s8-g: Mining of Real-world Hypergraphs: Patterns, Tools, and Generators
s8-h: Learning and Mining with Noisy Labels
7 - 9 PM
EDT
banquet
Key
research papers
applied papers
tutorials
industry day talks
poster/demo lightening
PhD symposium
Time
9 - 10 AM
EDT
Keynote: Divesh Srivastava (AT&T Research) - "Exploring and Analyzing Change: The Janus Project"
10:30 - 12:20 PM
EDT
S9-a: Personalization and Preference
S9-b: Architecture and Training
S9-c: Temporal Data
S9-d: Perturbations / Long-Tails
S9-e: Information extraction from social media: A hands-on tutorial on tasks, data, and open source tools
s9-f: Emerging Applications
S9-g: Finance & Healthcare
S9-h: Advertising & E-commerce
12:20 - 2 PM
EDT
lunch + business meeting  
2  - 3:30 PM
EDT
s10-a: Reinforcement Learning / Legal Informatics
s10-b: Fake News, Facts and Views
s10-c: Information Extraction
s10-d: Clustering
s10-e: Information extraction from social media: A hands-on tutorial on tasks, data, and open source tools
s10-f: Advertising & E-commerce
s10-g: Graph-based Management and Mining of Blockchain Data
s10-h: Fairness of Machine Learning in Search Engines
4 - 5:30 PM
EDT
S11–A: Neural Ranking
S11–b: Subgraphs and Substructure
S11–c: Search and Text
S11–d: Graphs & Recommendation
S11–e: Information extraction from social media: A hands-on tutorial on tasks, data, and open source tools
S11–f: Crowdsourcing
S11–G: Graph-based Management and Mining of Blockchain Data
S11–H: Fairness of Machine Learning in Search Engines
5:30  - 7 PM
EDT
poster (research/applied optional)
Key
research papers
applied papers
tutorials
industry day talks
poster/demo lightening
PhD symposium
Time
8 AM - 12 PM
EDT
Analyticup Day
Workshop: The Third workshop on Data-driven Intelligent Transportation
Workshop: The 2nd Workshop on Mixed-Initiative ConveRsatiOnal Systems
8 AM - 5:30 PM
EDT
Applied Machine Learning Methods for Time Series Forecasting (AMLTS)
Workshop: The 1st International Workshop on Federated Learning with Graph Data (FedGraph)
Deep Learning for Search and Recommendation
Workshop: AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence
TrustLOG: The First Workshop on Trustworthy Learning on Graphs
Workshop on Human-in-the-loop Data Curation
1 - 5:30 PM
EDT
Workshop: THECOG - Transforms in behavioral and affective computing
Workshop: PAS: Privacy Algorithms in Systems
Workshop: Workshop on Proactive and Agent-Supported Information Retrieval
Key
research papers
applied papers
tutorials
industry day talks
poster/demo lightening
PhD symposium