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Bridging the Gap between Information Science, Information Retrieval and Data Science

BIRDS 2020

URL: https://birds-ws.github.io/birds2020/
Event Date: 2020-07-30 ~ 2020-07-30
Submission Date: 2020-06-05
Location: Xi'an, China

Data Mining & Analysis Databases & Information Systems

(Apologies for cross-posting)
BIRDS - Bridging the Gap between Information Science, Information Retrieval and Data Science -
https://birds-ws.github.io/birds2020/index.html
An interdisciplinary SIGIR 2020 workshop for students, practitioners and researchers in Data Science, Information Retrieval and Information Science.
We are calling for papers for the BIRDS 2020 workshop and welcome you to join us online on 30th July 2020. BIRDS will be collocated with the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020, https://sigir.org/sigir2020/).
OVERVIEW
The overarching theme of the BIRDS workshop is to look at how DS, IR and IS can complement each other by applying a more holistic approach to these disciplines that go beyond traditional DS or IR or IS alone. BIRDS aims at extending the scope of current research to provide a view on data and information in all its quantity and variety through investigating user preferences and interaction. The cross-fertilization of DS, IR and IS that we want to address in this workshop goes three ways.
1. BIRDS will focus on the utilisation of DS methodologies in IR and IS, e.g. by integrating data mining, database concepts, heterogeneous data, data analysis, exploration and visualization techniques to IR and IS.
2. In addition, we will look at how user-oriented concepts and theories from IS, for instance, human-centric information seeking & searching, cognitive models (such as Information Foraging Theory or the Principle of Polyrepresentation), etc, can be applied to enhance and complement the data-driven approaches in DS and IR.
3. Finally, we will also examine how IR models and theory can apply to IS and DS, e.g. by introducing the concepts of vagueness and uncertainty, inherent in many IR models, to DS and IS.
To this aim, relevant topics of the workshop will be, but are not limited to:
IS models and theory applied to IR and DS
User modelling
Information Foraging
Cognitive Models
Interactive information access and retrieval
User preference and behavior analysis
User-centric exploratory data analysis
Evaluation methods for exploratory search and data analysis
Social and collaborative information seeking
Bibliometric-enhanced scholarly IR and data search
DS models and theory applied to IR and IS
Interpretability and explainability in its user-centric application
User-oriented Machine Learning and Deep Learning
User-centric data visualization
User-centric data exploration and mining
Data analysis for evaluation
IR models and theory applied to IS and DS
Multimodal information discovery
Database - IR integration
Query languages
Formal models for interactive heterogeneous data and information discovery
Conversational data exploration
The target audience of the workshop are students, practitioners and researchers in DS, IR and IS, from academia and industry alike.
SUBMISSIONS
Authors of accepted papers will be invited to present their papers orally at the (online) workshop and/or to present them in the interactive poster sessions. As we plan to publish the proceedings with CEUR Workshop Proceedings, all papers should be formatted in the Springer LNCS style (http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). Please adhere to a page limit of 12 pages excluding references. Submissions will be peer-reviewed by at least three members of the programme committee.
To submit your paper, please use our Easychair submission link at https://easychair.org/conferences/?conf=birds2020.
IMPORTANT DATES
Submission Deadline: 5th June 2020
Notification: 3rd July 2020
Camera-ready: 16th July 2020
If you have any further questions, you can reach out via email to birds2020@easychair.org.
ORGANIZERS
Ingo Frommholz, University of Bedfordshire, UK
Haiming Liu, University of Bedfordshire, UK
Massimo Melucci, University of Padova, Italy

Event Promotion

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Bridging the Gap between Information Science, Information Retrieval and Data Science

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