IMMM 2021

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IMMM 2021
The Eleventh International Conference on Advances in Information Mining and Management
Dates 2021-05-30 (iCal) - 2021-06-03
Homepage: https://www.iaria.org/conferences2021/IMMM21.html
Location:
Important dates
Submissions: 2021/03/02
Table of Contents


INVITATION:

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Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to: - IMMM 2021, The Eleventh International Conference on Advances in Information Mining and Management IMMM 2021 is scheduled to be May 30 - June 03, 2021 in Valencia, Spain under the DataSys 2021 umbrella. The submission deadline is March 2, 2021. Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: https://www.iariajournals.org

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======== IMMM 2021 | Call for Papers =========

CALL FOR PAPERS, TUTORIALS, PANELS

IMMM 2021, The Eleventh International Conference on Advances in Information Mining and Management

General page: https://www.iaria.org/conferences2021/IMMM21.html

Submission page: https://www.iaria.org/conferences2021/SubmitIMMM21.html

Event schedule: May 30 - June 03, 2021

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]


Submission deadline: March 2, 2021

Extended versions of selected papers will be published in IARIA Journals: https://www.iariajournals.org Print proceedings will be available via Curran Associates, Inc.: https://www.proceedings.com/9769.html Articles will be archived in the free access ThinkMind Digital Library: https://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 Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.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: https://www.iaria.org/editorialrules.html

IMMM 2021 Topics (for topics and submission details: see CfP on the site)

Call for Papers: https://www.iaria.org/conferences2021/CfPIMMM21.html

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IMMM 2021 Tracks (topics and submission details: see CfP on the site)

Trends in mining/retrieving/handling data Big data and Genome Data; Large scale data retrieval; Graph-modeled Data; Geo-tagged photos; Tractable uncertain data; Data curation workflow analysis; Online data integration services; Streaming/real-time/active; Stream processing at scale; Real-time analytics in the same database; Temporal mining; Temporal pattern discovery; Incrementally mining temporal patterns; Keyword search in large networks; Sequence mining with hierarchies; Phonetic time series; Mining communication motifs in dynamic environments; Approximate queries on string collection; Profiling entities; Data-intensive science using scalable analytics; Data-driven discovery; Composite dynamic-and-static indexing; Differential privacy on correlated data; Massive personal time-series clustering; Persistent data sketching; Stream data cleaning; Dynamic event streams; Out-of-Order data streams; Concept-drifting data streams; Indexing metrics for uncertain data; Mining and forecasting of Big time-series Data; Holistic indexing; Crowd mining; Mining subjective properties on the Web; Data semantics and information extraction; Community detection in social networks; Mining and learning activities; Confidence-based and incomplete information

Trends in methodologies/architectures/platforms Scalable classification frameworks; MapReduce over HybriD Clouds; Parallel Database Systems; Spatio-temporal and textual processing platforms; Deep language embedding; Large-Scale machine learning; Fault-tolerance for parallel data processing; Encrypted query processing; Enforcement of data use policies; Big Data industrial systems; Condensed representation; Temporal graphs; Graph summarization; Subspace and spectral methods; Cross-modal correlations; Open annotation data models; Elastic processing of data streams; Interactive data transformation; On-line aggregation; Interactive analysis on Big Data; Crowdsourcing applications; Distributed online tracking; Social graph partitioning methods; Monitoring of co-evolving data streams; Deep packet inspection systems; Ensemble-based data mining platforms; Sensors-oriented time-series prediction systems; Social multimedia as sensors; Sentiment representation systems

Mining mechanisms and methods Contextual aggregated information retrieval; Aggregated query for workflows; 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

Short video/links scientific content Apps; Mobile social media; Video production; Innovative video content; Creative process; Dedicated apps; Special apps for short scientific reports; Techniques for a convincing summary report; Mobile and wearable devices for scientific reports; Combining open space and lab space in scientific reports; Handling inventories of short video scientific reports; Innovative mobile content; Online news; Volatile and just-in-time news; Report authenticity; Copyright and authorship; Ethical aspects; etc.

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; Managing 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

  • AICT 2021 Publicity Chairs*

Marta Botella-Campos, Universitat Politecnica de Valencia, Spain Daniel Basterretxea, Universitat Politecnica de Valencia, Spain

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