CIKM 2014 - 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014)

The 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014) will be held from Nov 3-7, 2014 in Shanghai, China. CIKM is a top-tier ACM conference in the areas of information retrieval, knowledge management and databases. Since 1992, it has successfully brought together leading researchers and developers from the three communities. The purpose of the conference is to identify challenging problems facing the development of future knowledge and information systems, and to shape future research directions through the publication of high quality, applied and theoretical research findings. In CIKM 2014, we will continue the tradition of promoting collaboration among multiple areas. We encourage submissions of high quality research papers and posters on all topics in the general areas of databases, information retrieval, and knowledge management.
Topics of Interest
Topics of interest of CIKM2014 include, but are not limited to, the following areas in three distinct tracks:
Database Track
Applications and Experiences? ?
Cloud Computing and Big Data Analytics?
Data Integration and Data Provenance?
Knowledge Base and Semantic Network?
Main-memory, Real-time, Parallel and Distributed Database Systems
Query Language, Query Processing, Access Methods, and Concurrency Control
Security and Privacy
Stream Data and Event Processing?
Spatial, Temporal, Multimedia, and Mobile Data Management
Semi-structured and Unstructured Data Management and Analytics
Uncertain, Probabilistic, and Scientific Data Management?
Web and Social Data Management
Information Retrieval Track
Adversarial IR and Spam
Collaborative, Crowd-Based, and Game-Based Approaches to IR
Computations Linguistics for IR (QA, Summarization, Extraction)
Cross-language and Multilingual IR
Distributed and Peer-to-Peer IR
Domain-specific IR (legal, genome, chemical, etc)
Filtering, Time-Sensitive and Real-time Search
Foundations of Information Retrieval
IR Approaches to Computational Advertising
IR Architectures, Scalability and Efficiency
IR Evaluation
Machine Learning for IR
Mobile Search
Multimedia IR (Audio, Speech, Video, Image)
Novel IR Interfaces (Exploratory, Interactive, Accessible)
Personalized Search
Semantic and Entity-Based IR
Semi-Structured Information Retrieval
Social Networks and IR
User Studies, Click Models, Interaction Models
Knowledge Management Track
Clustering, Classification, and Ranking
Data Mining and Knowledge Management for Bioinformatics
Data Mining Theory, Methods, and Applications
Information Filtering and Recommender Systems
Knowledge Representation, Reasoning, and Visualization
Large-Scale Machine Learning and Statistical Techniques
Mining Big Data and Streams
Personalization, Advertising, and Search
Secure and Privacy-Preserving Data Mining
Social Networks and Social Media
Spatial, Temporal, and Graph Data Mining
Text and Web Data Mining
Time-Series and Pattern Mining