Información de la conferencia

WSDM 2027: International Conference on Web Search and Data Mining

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WSDM
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Día de Entrega:
2026-08-17
Fecha de Notificación:
2026-11-02
Fecha de conferencia:
2027-02-15
Ubicación:
Hong Kong, China
Ediciones:
CCF: B   ICORE: A   QUALIS: B1   Vistas: 348266   Seguidores: 319   Asistentes: 47

Índice Conference Partner (CP-I)

89,8 / 100
Puesto n.º 66 de 5.682 congresos · 2% superior

N.º 3 de 253 en Sistemas de información y Web N.º 5 de 337 en Minería de datos y bases de datos

Reconocimiento académico (35%)
88
Selectividad en la revisión (20%)
94
Ediciones celebradas (20%)
82
Atención de la comunidad (10%)
88
Integridad del registro público (15%)
100

Datos utilizados: Categorías: CCF B, ICORE A, QUALIS B1 · Tasa de aceptación: 16.7% (media de 5 ediciones registradas) · Ediciones documentadas: 20 · Investigadores que lo siguen aquí: 319 · Investigadores que abrieron esta página en los últimos 24 meses: 79

Confianza 100 %: la parte de la puntuación respaldada por datos observados y no por la línea base neutra. Cómo se calcula esta puntuación · Ver la clasificación · Versión del algoritmo 1.1 · Calculado el 2026-09-19

Solicitud de Artículos

WSDM 2027 (International Conference on Web Search and Data Mining) is a CCF B / ICORE A / QUALIS B1 conference held in Hong Kong, China on 2027-02-15. The paper submission deadline is 2026-08-17. Acceptance notifications are sent on 2026-11-02.

List of Topics Papers accepted to WSDM will be published in the ACM Digital Library. We invite submissions on a broad range of topics related to search and data mining on the Web and Social Web. Areas of interest include, but are not limited to, the following 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. Web Mining and Content Analysis Crawling and indexing web content; Web recommender systems and algorithms; Agentic recommender systems; 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; Scalable algorithms for mining web data; Opinion mining and sentiment analysis; Web traffic and log analysis; Web measurements, web evolution, and web models; Generative web applications; Foundation Models and Agentic Systems LLMs and multimodal foundation models for web tasks; Generative question answering and reasoning; Retrieval, indexing, and ranking with foundation models; Evaluation and benchmarking of foundation models in search/mining; Web agents; GUI agents/multi-agent systems in Web search, recommendation, and interactive information retrieval; Continual learning and self-evolution; Memory systems of foundation models; User interfaces and experiences powered by foundation models. Web of Things, Ubiquitous and Mobile Computing Geo-location data analysis; Mobility and behavior data mining; Location-based social networks; User activity modeling and exploitation. Privacy, Fairness, Interpretability Fairness and accountability in ranking, recommendations and advertising; Explainability in web systems; Model and algorithm transparency; 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. 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, and coordinated behavior; Polarization, extremism and radicalization; Echo chambers and filter bubbles. Emerging and Creative Applications Systems and algorithms for urban applications such as smart cities/digital twins; Climate, sustainability, and environmental intelligence systems; Online education systems; Monitoring and prevention of epidemics; Healthcare and clinical decision support; Embodied AI systems interacting with web and real-world environments; AI for Data-rich Science; Scientific Foundation Models.
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Tasa de aceptación

Tasa de aceptación media: 16.8% en 10 años (2014–2023).

AñoEnviadosAceptadosAceptados(%)
202369012317.8%
20225058015.8%
202160311218.6%
20206159114.8%
20195118416.4%
20185148416.3%
20175058015.8%
20163686718.2%
20152383916.4%
20143556418%

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