KDD-2015 Call for Papers, Workshop Proposals

KDD-2015, the premier research conference on Data Mining and Data Science, invites submissions of research papers, practice track papers, workshop proposals.

KDD-2015, Sydney, 10-13 Aug 2015 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Sydney, Australia, Aug 10-13, 2015.

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) is a premier conference that brings together researchers and practitioners from data mining, knowledge discovery, data analytics, and big data.

Submissions to KDD 2015 are solicited on all aspects of knowledge discovery and data mining.

Key dates:
  • Paper submission due: February 20, 2015
  • Acceptance notification: May 12, 2015

KDD is a dual track conference hosting both a Research track and a Practice track as outlined below. A more detailed CFP that includes reviewing criteria, formatting guidelines, the dual submission policy, etc. is available at www.kdd.org/kdd2015/calls.html.

Research track papers

The Research Track invites 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 significant advances over existing approaches.

Papers submitted to the Research Track are solicited in all areas of data mining, knowledge discovery, and large-scale data analytics, including, but not limited to:
  • Big Data: Efficient and distributed data mining platforms and algorithms, systems for large-scale data analytics of textual and graph data, large-scale machine learning systems, distributed computing (cloud, map-reduce, MPI), large-scale optimization, and novel statistical techniques for big data.
  • Data Science: Methods for analyzing scientific data, business data, social network analysis, recommender systems, mining sequences, time series analysis, online advertising, bioinformatics, systems biology, text/web analysis, mining temporal and spatial data, and multimedia processing.
  • Foundations of Data Mining: Data mining methodology, data mining model selection, visualization, asymptotic analysis, information theory, security and privacy, graph and link mining, rule and pattern mining, web mining, dimensionality reduction and manifold learning, combinatorial optimization, relational and structured learning, matrix and tensor methods, classification and regression methods, semi-supervised learning, and unsupervised learning and clustering.

Practice track papers

The Practice Track invites submissions of papers describing research and implementations of data mining/data analytics/big data/data science solutions and systems for practical tasks and practical settings. The application domains of interest include, but are not limited to education, public policy, industry, government, healthcare, e-commerce, telecommunications, law, or non-profit settings. Our primary emphasis is on papers that advance the understanding of, and show how to deal with, practical issues related to deploying analytics technologies. This track also highlights new research challenges motivated by analytics and data mining applications in the real world.

Submitted papers will go through a competitive peer review process. The Practice Track (formerly known as the "Industry and Government Track") is distinct from the Research Track in that submissions solve real-world problems and focus on systems that are deployed or are in the process of being deployed. Submissions must clearly identify one of the following three areas they fall into: "deployed", "discovery", or "emerging".

For criteria for submissions and more information, visit

KDD 2015 Call for Workshop Proposals

The KDD 2015 organizing committee solicits proposals for full-day and half-day workshops to be held in conjunction with the main conference. The purpose of a workshop is to provide an opportunity for participants from academia, industry, government and other related parties to present and discuss novel ideas on current and emerging topics relevant to knowledge discovery and data mining. Workshops are (tentatively) scheduled for August 10, 2015.


Each workshop should be organized under a well-defined theme focusing on emerging research areas, challenging problems and industrial/governmental applications. Organizers have free controls on the format, style as well as building blocks of the workshop. Possible contents of a workshop include but are not limited to invited talks, regular papers/posters, panels, and other pragmatic alternatives. In case workshop proposers need extra time to prepare their workshop, early decisions may be considered if justified.

The goal of the workshops is to provide an informal forum to discuss important research questions and practical challenges in data mining and related areas. Novel ideas, controversial issues, open problems and comparisons of competing approaches are strongly encouraged as workshop topics. In particular, we would like to encourage organizers to avoid a mini-conference format by (i) encouraging the submission of position papers and extended abstracts, (ii) allowing plenty of time for discussions and debates, and (iii) organizing workshop panels.


Possible workshop topics include all areas of data mining and knowledge discovery, machine learning, statistics, and data and information sciences, but are not limited to these. Interdisciplinary workshops with applications of data mining and data sciences to various disciplines (such as health, medicine, biology, sustainability, ecology, social sciences, humanities, or aerospace) are of high interest.

For more info and submission details, see


Workshop proposals should be emailed to workshops2015@kdd.org by March 6, 2015 at 11:59 PM Pacific Standard Time.