CALL FOR PAPERS, TUTORIALS, PANELS
IMMM 2016, The Sixth International Conference on Advances in Information Mining and Management
General page: http://www.iaria.org/
Submission page: http://www.iaria.org/
DATASETS 2016, The International Symposium on Designing, Validating, and Using Datasets
General page: http://www.iaria.org/
Submission page: http://www.iaria.org/
Events schedule: May 22 – 26, 2016 – Valencia, Spain
Contributions:
– regular papers [in the proceedings, digital library]
– short papers (work in progress) [in the proceedings, digital library]
– ideas: two pages [in the proceedings, digital library]
– extended abstracts: two pages [in the proceedings, digital library]
– posters: two pages [in the proceedings, digital library]
– posters: slide only [slide-deck posted at www.iaria.org]
– presentations: slide only [slide-deck posted at www.iaria.org]
– demos: two pages [posted at www.iaria.org]
– doctoral forum submissions: [in the proceedings, digital library]
Proposals for:
– mini symposia: see http://www.iaria.org/
– workshops: see http://www.iaria.org/workshop.
– tutorials: [slide-deck posed on www.iaria.org]
– panels: [slide-deck posed on www.iaria.org]
Submission deadline: January 5, 2016
Sponsored by IARIA, www.iaria.org
Extended versions of selected papers will be published in IARIA Journals: http://www.iariajournals.org
Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/
Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org
The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.
All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels.
Before submission, please check and comply with the editorial rules: http://www.iaria.org/
IMMM 2016 Topics (for topics and submission details: see CfP on the site)
Call for Papers: http://www.iaria.org/
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Mining mechanisms and methods
Data mining algorithms; Media adaptive mining; Agent-based mining; Content-based mining; Context-aware mining; Automation of data extraction; Data mining at a large; Domain-driven data mining; Graph-based data mining; Multilabel information; Multimodal mining; Cloud-based mining; Mining using neurocomputing techniques
Mining support
Querying for mining; Questions for digital investigation; Similarity search; User-generated content; Visualizing data mining; Internationalization and localization techniques for profile/context-based visualization
Type of information mining
Concept mining; Process mining; Concept mining; Knowledge mining; Knowledge discovery; Mining image and video; Mining patterns; Opinion mining; Graph mining; Ontology mining; Semantic annotations and mining; Document mining; Spatial mining; Speech mining; Text mining; Web mining; XML data mining
Pervasive information retrieval
Context and location information retrieval; Mobile information retrieval; Geo-information retrieval; Context-aware information retrieval; Access-driven information retrieval; Location-specific information retrieval; Spacial information retrieval; Semantic-driven retrieval
Automated retrieval and mining
Automated information extraction; Agent-based data mining and information discovery; Agent-based knowledge; Datamining-based agents and multi-agent systems; Agent-mining intelligent applications and systems; Automated retrieval of multimedia streams; Automated retrieval from multimedia archives; Automated copyright infringement detection and watermarking; Automated content summarization; Automatic concept detection, categorization, and genre detection; Automatic speech recognition; Automated cross-media linking
Mining features
Dimensionality reduction; Feature weighting; Subset selection; Feature extraction; Feature construction; Data streams and time series; Selection in high-dimensional domains; Multilingual data mining; Multimedia mining; String processing and data mining; Mining association rules; Mining social relationships; Mining linked data; Mining sequential episodes from time series; Mining time-dependent data; Un-supervised data mining; Semi-structured data; Mining location-sensitive data; Concept-drift in data mining
Information mining and management
Data cleaning; Data updating; Segmentation and clustering; Mining transient information; Warehousing; Web syndication; Data filtering and aggregation; Optimal pruning; Data summarization; Knowledge injection, discovery and classification; Uncertainty removal; Managing incompleteness
Mining from specific sources
Bio data mining; Climate data mining; Data mining in medicine and pharmacology; Data mining in special networks (grids, sensors, etc.); Data management for mobile systems; Data management for sensors; Data mining and management for wireless systems; Dynamic network discovery; Mining from multiple sources; Mining personal semantic data; Mining from social networks; Mining from deep web; Mining from Wikipedia
Data management in special environments
Data management in sensor and mobile ad hoc networks; Data management in mobile peer-to-peer networks; Data management for mobile applications; Data management in mobile/temporal social networks; Management of community sensing/participatory sensing data; Managing pervasive data, sensor data streams and user devices; Managing mobile semantic data; Manging data-intensive mobile computing; Management of real-time data; Managing security data streams; Managing Mobile Web 2.0 data; Managing data in mobile clouds; Data replication, migration and dissemination in mobile environments; Web data processing and security on mobile devices; Resource advertising and discovery techniques
Mining evaluation
Statistics on mining; Ranking of mining results; Provenance; Privacy issues; Patterns for mining; Credibility on data mining; Performance of mining information; Data mining and computational intelligence; Intelligent data understanding; Intelligent data analysis
Mining tools and applications
Data mining applications; Data mining tools and enabling software; Interoperability of information mining tools; Applications for large-scale mining; Content segmentation tools (e.g., shot and semantic scene segmentation); Evaluation methods for TV and radio content analysis tools; Tools for data sets and standard resources
DATASETS 2016 Topics (for topics and submission details: see CfP on the site)
CfP: http://www.iaria.org/
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THEORY
The anatomy of designing Datasets
Designing context-based Datasets
Metadata for Datasets
Challenges in designing very large Datasets
Updatable and updating Datasets
Reference Datasets
Datasets families
Repositories of Datasets
Criteria for selecting appropriate Datasets
TYPES
Public and private Datasets
Open Datasets
Big Data and Datasets
Trusted Datasets
Mining massive Datasets
FEATURES
Testing and validating Datasets
Pitfalls with Datasets
Reputation of Datasets
Accuracy estimation of Datasets
Data links in Datasets
APPLICATIONS AND EXPERIMENTS
Context-aware Datasets in the Internet of Things
Datasets for data mining
Datasets used in statistics and machine learning
Online Datasets on collective behavior
Datasets for analytics and knowledge discovery
Regression Datasets
Climate Datasets
Gene Datasets
Health Datasets
Economic Datasets
Social Datasets
Transportation Datasets
Urban Datasets
Education/scholar Datasets
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IMMM 2016 Committee: http://www.iaria.org/
DATASETS 2016 Committee: http://www.iaria.org/