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WSDM 2025 : 18th ACM International Conference on Web Search and Data Mining

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Conference Series : Web Search and Data Mining
 
Link: https://www.wsdm-conference.org/2025/call-for-papers/
 
When Mar 10, 2025 - Mar 14, 2025
Where Hannover, Germany
Abstract Registration Due Aug 7, 2024
Submission Deadline Aug 14, 2024
Notification Due Oct 23, 2024
Final Version Due Dec 18, 2024
Categories    web search   data mining   web of things   intelligent assistants
 

Call For Papers

WSDM is a highly selective conference that includes invited talks, as well as refereed full papers. WSDM publishes original, high-quality papers related to search and data mining on the Web and the Social Web, with an emphasis on practical yet principled novel models of search and data mining, algorithm design and analysis, economic implications, and in-depth experimental analysis of accuracy and performance.

WSDM 2025 will take place in Hannover, the capital of the German state of Lower Saxony.

List of Topics

Web Search
Algorithms for web-scale search; Adversarial search; Search user interfaces and interaction; Distributed search, metasearch, peer-to-peer search; Local and mobile search; Multimedia web search, cross-lingual search; Query analysis and query processing; Search benchmarking and evaluation; Search user behavior and log analysis; Search with Foundation Models

Web Mining and Content Analysis
Crawling and indexing web content; Web recommender systems and algorithms; Clustering, classification, and summarization of web data; Data, entity, event, and relationship extraction; Knowledge acquisition and automatic construction of knowledge bases; Large-scale graph analysis; Semantic search, faceted search, and knowledge graphs; Multimodal data mining; Scalable algorithms for mining web data; Opinion mining and sentiment analysis; Web traffic and log analysis; Web measurements, web evolution, and web models.

Web of Things, Ubiquitous and Mobile Computing
Algorithms for web-scale search; Adversarial search; Search user interfaces and interaction; Distributed search, metasearch, peer-to-peer search; Local and mobile search; Multimedia web search, cross-lingual search; Query analysis and query processing; Search benchmarking and evaluation; Search user behavior and log analysis; Search with Foundation Models

Privacy, Fairness, Interpretability
Fairness and accountability in ranking, recommendations and advertising; Explainability in web systems; Model and algorithm transparency; Interpretable models of individual and social behavior; Web search and data mining under privacy constraints; Fairness and interpretability in applications of web mining for social good.

Social Networks
Link prediction and community detection; Social network analysis and graph algorithms; Computational social science; Influence and viral marketing in social networks; Social sensing; Searching social and real-time content; Social network dynamics; Sampling, experiments, and evaluation in social networks; Social media analysis: blogs and friendship networks; Social network analysis, theories, models and applications; Social reputation and trust.

Intelligent Assistants
Voice search, conversational search, and dialog systems; Personal assistants, dialogue models, and conversational interaction; Task-driven search; Zero-query and implicit search.

Crowdsourcing and Human Computation
Collaborative search and question answering; Human-in-the-Loop and Collaborative Human-AI systems.

Emerging and Creative Applications
Mental health and well-being support systems; Web mining for social good; Systems and algorithms for urban applications such as smart cities/buildings/etc; Online education systems; Monitoring and prevention of epidemics; Social chatbots.

Information Integrity
Systems and algorithms for monitoring and detection of misinformation and fake news; Prevalence and virality of misinformation; Misinformation sources and origins; Source and content credibility; Detecting and combating spamming, trolling, aggression, dog whistles, and toxic online behaviors; Methods for detecting and mitigating low quality and offensive content, bullying and hate speech; Polarization, extremism and radicalization; Echo chambers and filter bubbles.

Foundation Models
Use of large language models (LLMs) and other foundation models for web search and data mining, including but not limited to the following tasks: Generative question answering; Indexing and query analysis; Pre-training and self-supervised learning for web-based tasks; Development of new user interfaces and user experiences; Support to information integrity.

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