KDIR 2019 : 11th International Conference on Knowledge Discovery and Information Retrieval
CALL FOR PAPERS
11th International Conference on Knowledge Discovery and Information Retrieval KDIR
September 17 – 19, 2019 Vienna, Austria
Proceedings will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS, Semantic Scholar and Google Scholar.
Regular Paper Submission: April 29, 2019
Authors Notification (regular papers): June 28, 2019
Final Regular Paper Submission and Registration: July 12, 2019
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. Information retrieval (IR) is concerned with gathering relevant information from unstructured and semantically fuzzy data in texts and other media, searching for information within documents and for metadata about documents, as well as searching relational databases and the Web. Automation of information retrieval enables the reduction of what has been called “information overload”. Information retrieval can be combined with knowledge discovery to create software tools that empower users of decision support systems to better understand and use the knowledge underlying large data sets. The primary focus of KDIR is to provide a major forum for the scientific and technical advancement of knowledge discovery and information retrieval.
Area 1: KDIR – International Conference on Knowledge Discovery and Information Retrieval
– BioInformatics & Pattern Discovery
– Foundations of Knowledge Discovery in Databases
– Information Extraction
– Interactive and Online Data Mining
– Machine Learning
– Mining Multimedia Data
– Mining Text and Semi-structured Data
– Pre-processing and Post-processing for Data Mining
– Process Mining
– Software Development
– Structured Data Analysis and Statistical Methods
– Business Intelligence Applications
– User Profiling and Recommender Systems
– Visual Data Mining and Data Visualization
– Web Mining
– Clustering and Classification Methods
– Collaborative Filtering
– Concept Mining
– Context Discovery
– Data Analytics
– Data Mining in Electronic Commerce
– Data Reduction and Quality Assessment
KDIR CONFERENCE CHAIR:
Joaquim Filipe, Polytechnic Institute of Setúbal / INSTICC, Portugal
KDIR PROGRAM CHAIR:
Ana Fred, Instituto de Telecomunicações and Instituto Superior Técnico – Lisbon University, Portugal
Address: Avenida de São Francisco Xavier Lote 7L Cave
Tel: +351 265 520 184
Fax: +351 265 520 186
KDD 2019 : 25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING
KDD 2019 Call for Research Papers
Details in https://www.kdd.org/kdd2019/calls/view/kdd-2019-call-for-research-papers
Website for submissions: https://easychair.org/conferences/?conf=kdd2019 .
Submission: February 3, 2019
Notification: Apr 28, 2019
Camera-ready: May 17, 2019
Short Promotional Video (Required): June 2, 2019
Conference (Anchorage, Alaska): August 4 to August 8, 2019
We invite submission of papers describing innovative research on all aspects of knowledge discovery and data mining, ranging from theoretical foundations to novel models and algorithms for data mining problems in science, business, medicine, and engineering. Visionary papers on new and emerging topics are also welcome, as are application-oriented papers that make innovative technical contributions to research. Authors are explicitly discouraged from submitting incremental results that do not provide major advances over existing approaches
All deadlines are at 11:59PM Alofi Time. There will be absolutely no exception to these deadlines.
Topics of interest include, but are not limited to:
Big Data: Large-scale systems for text and graph analysis, machine learning, optimization, parallel and distributed data mining (cloud, map-reduce), novel algorithmic and statistical techniques for big data.
Data Science: Methods for analyzing scientific and business data, social networks, time series; mining sequences, streams, text, web, graphs, rules, patterns, logs data, spatio-temporal data, biological data; recommender systems, computational advertising, multimedia, finance, bioinformatics.
Foundations: Models and algorithms, asymptotic analysis; model selection, dimensionality reduction, relational/structured learning, matrix and tensor methods, probabilistic and statistical methods; deep learning; manifold learning, classification, clustering, regression, semi-supervised and unsupervised learning; personalization, security and privacy, visualization.
KDD is a dual track conference hosting both a Research track and an Applied Data Science track. Due to the large number of submissions, papers submitted to the Research track will not be considered for publication in the Applied Data Science track and vice versa. Authors are encouraged to read the track descriptions carefully and to choose an appropriate track for their submissions. Submissions are limited to a total of nine (9) pages, including all content and references, and must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. For LaTeX users: unzip acmart.zip, make, and use sample-sigconf.tex as a template;
Additional information about formatting and style files is available online at: https://www.acm.org/publications/proceedings-template.
Papers that do not meet the formatting requirements will be rejected without review. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file and start at page 10) focused on reproducibility. This supplement can only be used to include (i) information necessary for reproducing the experimental results, insights, or conclusions reported in the paper (e.g., various algorithmic and model parameters and configurations, hyper-parameter search spaces, details related to dataset filtering and train/test splits, software versions, detailed hardware configuration, etc.), and (ii) any pseudo-code, or proofs that due to space limitations, could not be included in the main nine-page manuscript, but that help in reproducibility (see reproducibility policy below for more details).
The Research track follows a double-blind review process. Submitted papers must not include author names and affiliations and they must be written in a way so that they do not break the double-blind reviewing process. Papers that violate the double-blind review requirements will be desk rejected.
Because of the double-blind review process, non-anonymous papers that have been issued as technical reports or similar, in particular in arXiv, either prior to KDD submission or during the review process, cannot be submitted to the research track.
Website for submissions: https://easychair.org/conferences/?conf=kdd2019 .
Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. Authors are strongly encouraged to make their code and data publicly available whenever possible. In addition, authors are strongly encouraged to also report, whenever possible, results for their methods on publicly available datasets. Algorithms and resources used in a paper should be described as completely as possible to allow reproducibility. This includes experimental methodology, empirical evaluations, and results. The authors are encouraged to take advantage of the optional two-page supplement to provide the appropriate information. The reproducibility factor will play an important role in the assessment of each submission.
Important Note: To encourage reproducibility of the results presented in KDD, only papers that include this two-page supplement with the necessary reproducibility-related information will be considered for the best paper awards.
Every person named as the author of a paper must have contributed substantially both to the work described in the paper and to the writing of the paper. Every listed author must take responsibility for the entire content of a paper. Persons who do not meet these requirements may be acknowledged, but should not be listed as authors. Post-submission changes to the author list are not allowed.
No dual submissions are allowed. Submitted papers must describe work that is substantively different from work that has already been published, or accepted for publication, or submitted in parallel to other conferences or journals.
Conflicts of Interest
During the submission process, enter the email domains of all institutions with which you have an institutional conflict of interest. You have an institutional conflict of interest if you are currently employed or have been employed at this institution in the past three years, or you have extensively collaborated with this institution within the past three years. Authors are also required to identify all PC/SPC members with whom they have a conflict of interest, e.g., advisor, student, colleague, or coauthor in the last five years.
Additional information about ACM’s Conflict of Interest policy, which KDD follows, can be found at https://www.acm.org/publications/policies/conflict-of-interest.
KDD follows ACM’s policies, which are described at https://www.acm.org/publications/policies/retraction-policy .
For each accepted paper, at least one author must attend the conference and present the paper. Authors of all accepted papers must prepare a final version for publication, a poster, and a three-minute short video presentation (details will be in the acceptance notification).
Accepted papers will be published in the conference proceedings by ACM and also appear in the ACM Digital Library. The rights retained by authors who transfer copyright to ACM can be found here.
AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available in the ACM Digital Library. This date for KDD 2019 is on or after July 11, 2019. The official publication date affects the deadline for any patent filings related to published work.
George Karypis and Evimaria Terzi
Research Track PC co-Chairs of KDD-2019
ICKE–Ei Compendex, Scopus 2020 : 2020 6th International Conference on Knowledge Engineering (ICKE 2020)–Ei Compendex, Scopus
Welcome to ICKE 2020
2020 6th International Conference on Knowledge Engineering (ICKE 2020) will be held in Okayama, Japan during March 28-30, 2020, ICKE 2020 is sponsored by Okayama University, Japan.
Peer reviewed and presented papers will be published in the International Conference Proceedings, which will indexed by **Ei Compendex** and **Scopus**.
Topics of interest for submission include, but are not limited to:
Education and Training Issues
Natural language processing
Process knowledge and semantic services
More detail about topics, please visit：http://www.icke.org/sub.htm
1. Full Paper (Presentation and publication)
2. Abstract (Presentation only)
Please log in the Electronic Submission System(http://confsys.iconf.org/submission/icke2020)
or submit paper to: firstname.lastname@example.org
More detail about submission, please visit: http://www.icke.org/sub.htm
Okayama University, Japan
Address: １丁目-1-1 Tsushimanaka, Kita Ward, Okayama, 700-8530
Academic Visiting or One day Tour will be arranged during March 30, 2020 in Okayama, Japan.
Ms. Teri Zhang, Conference Secretary