posted by user: Calendar_Sites || 17023 views || tracked by 41 users: [display]

KDIR 2011 : KDIR- International Conference on Knowledge Discovery and Information Retrieval

FacebookTwitterLinkedInGoogle


Conference Series : International Conference on Knowledge Discovery and Information Retrieval
 
Link: http://www.kdir.ic3k.org/
 
When Oct 26, 2011 - Oct 29, 2011
Where Paris, France
Submission Deadline May 10, 2011
Notification Due Jul 6, 2011
Final Version Due Jul 22, 2011
Categories    knowledge discovery   information retrieval
 

Call For Papers

Conference name: KDIR- International Conference on Knowledge Discovery and Information Retrieval

Venue: Paris, France


Event Date:26-29 October, 2011


Scope

Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from data, often based on underlying large data sets. A major aspect of Knowledge Discovery is data mining, i.e. applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge. This has proven to be a promising approach for enhancing the intelligence of software systems and services. The ongoing rapid growth of online data due to the Internet and the widespread use of large databases have created an important need for knowledge discovery methodologies. The challenge of extracting knowledge from data draws upon research in a large number of disciplines including statistics, databases, pattern recognition, machine learning, data visualization, optimization, and high-performance computing, to deliver advanced business intelligence and web discovery solutions.

Conference Topics

* Information Extraction
* Machine Learning
* Concept Mining
* Context Discovery
* Foundations of Knowledge Discovery in Databases
* Data Analytics
* Optimization
* Interactive and Online Data Mining
* Process Mining
* Integration of Data Warehousing and Data Mining
* Data Reduction and Quality Assessment
* Pre-processing and Post-processing for Data Mining
* Mining High-dimensional Data
* Mining Text and Semi-structured Data
* Information Extraction from Emails
* Mining Multimedia Data
* Web Mining
* User Profiling and Recommender Systems
* Collaborative Filtering
* Structured Data Analysis and Statistical Methods
* BioInformatics & Pattern Discovery
* Clustering and Classification Methods
* Visual Data Mining and Data Visualization
* Software Development
* Business Intelligence Applications
* Data Mining in Electronic Commerce



IMPORTANT DATES

› Conference date: 26-29 October, 2011

Regular Paper Submission: May 10, 2011
Authors Notification (regular papers): July 6, 2011
Final Regular Paper Submission and Registration: July 22, 2011

SECRETARIAT

KDIR Secretariat

Address: Av. D. Manuel I, 27A, 2º esq.
2910-595 Setúbal - Portugal

Tel.: +351 265 100 033

Fax: +44 203 014 8639

e-mail: kdir.secretariat@insticc.org

Web: http://www.kdir.ic3k.org/

Related Resources

KDIR 2024   16th International Conference on Knowledge Discovery and Information Retrieval
IEEE-Ei/Scopus-SGGEA 2024   2024 Asia Conference on Smart Grid, Green Energy and Applications (SGGEA 2024) -EI Compendex
PAKDD 2025   29th Pacific-Asia Conference on Knowledge Discovery and Data Mining
KDIR 2024   16th International Conference on Knowledge Discovery and Information Retrieval
SPIE-Ei/Scopus-DMNLP 2025   2025 2nd International Conference on Data Mining and Natural Language Processing (DMNLP 2025)-EI Compendex&Scopus
ecml-pkdd-journal-track 2025   Journal Track with ECML PKDD 2025
Ei/Scopus-ACAI 2024   2024 7th International Conference on Algorithms, Computing and Artificial Intelligence(ACAI 2024)
ICPRAM 2025   14th International Conference on Pattern Recognition Applications and Methods
ICKEA 2025   2025 The 10th International Conference on Knowledge Engineering and Applications (ICKEA 2025)
AMLDS 2025   IEEE--2025 International Conference on Advanced Machine Learning and Data Science