SUM 2020 : he 14th International Conference on Scalable Uncertainty Management

Established in 2007, the SUM conferences are annual events which aim to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as Artificial Intelligence and Machine Learning, Databases, Information Retrieval and Data Mining, the Semantic Web and Risk Analysis, and with the aim of fostering collaboration and cross-fertilization of ideas from the different communities. An originality of the SUM conferences is their care for dedicating a large space of their program to tutorials covering a wide range of topics related to uncertainty management. Each tutorial provides a survey of one of the research areas in the scope of the conference.

The 14th International Conference on Scalable Uncertainty Management (SUM 2020) will be held in Bolzano, Italy from September 23-25, 2020.

Topics of interest

We solicit papers on the management of large amounts of complex kinds of uncertain, incomplete, or inconsistent information. We are particularly interested in papers that focus on bridging gaps, for instance between different communities, between numerical and symbolic approaches, or between theory and practice. Topics of interest include (but are not limited to):

Imperfect information in databases

* Methods for modeling, indexing, and querying uncertain databases

* Top-k queries, skyline query processing, and ranking

* Approximate, fuzzy query processing

* Uncertainty in data integration and exchange

* Uncertainty and imprecision in geographic information systems

* Probabilistic databases and possibilistic databases

* Data provenance and trust

* Data summarization

* Very large datasets

Imperfect information in information retrieval and semantic web applications

* Approximate schema and ontology matching

* Uncertainty in description logics and logic programming

* Learning to rank, personalization, and user preferences

* Probabilistic language models

* Combining vector-space models with symbolic representations

* Inductive reasoning for the semantic web

Imperfect information in artificial intelligence

* Statistical relational learning, graphical models, probabilistic inference

* Argumentation, defeasible reasoning, belief revision

* Weighted logics for managing uncertainty

* Reasoning with imprecise probability, Dempster-Shafer theory, possibility theory

* Approximate reasoning, similarity-based reasoning, analogical reasoning

* Planning under uncertainty, reasoning about actions, spatial and temporal reasoning

* Incomplete preference specifications

* Learning from data

Risk analysis

* Aleatory vs. epistemic uncertainty

* Uncertainty elicitation methods

* Uncertainty propagation methods

* Decision analysis methods

* Tools for synthesizing results

Submission Guidelines

SUM 2020 solicits original papers in the following three categories:

(1) Long papers (14 pages): technical papers reporting original research or survey papers

(2) Short papers (8 pages): papers reporting promising work-in-progress, system descriptions, position papers on controversial issues, or survey papers providing a synthesis of some current research trends

(3) Extended abstracts (2 pages) of recently published work in a relevant journal or top-tier conference

All SUM submissions must be formatted according to the LNCS/LNAI guidelines: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines

Papers should be submitted via EasyChair:

https://easychair.org/conferences/?conf=sum2020

Dates

All Deadlines are 23:59 Central European Time.

April 22nd, 2020: Submission deadline

June 10th, 2020: Notification

June 26th, 2020: Camera-ready copies due

Sept. 23rd-25th, 2020: Conference

Publication

Accepted long (14 pages) and short papers (8 pages) will be published by Springer in the Lecture Notes in Artificial Intelligence (LNAI) series. Authors of an accepted long or short paper will be expected to sign copyright release forms, and one author is expected to give a presentation at the conference. Authors of accepted abstracts (2 pages) will be expected to present their work during the conference, but the extended abstracts will not be published in the LNCS/LNAI proceedings (they will be made available in a separate booklet)