BIRDS 2021

Bridging the Gap between Information Science, Information Retrieval and Data Science
https://birds-ws.github.io/birds2021/index.html

An interdisciplinary CHIIR 2021 workshop for students, practitioners and researchers in Data Science, Information Retrieval, Information Science and Human-Computer Interaction.

March 19, 2021 (online)

Registration: https://web.cvent.com/event/c718c2f6-51e3-4f11-bd86-625d0ba8fb2e/summary

BIRDS offers a range of invited talks and accepted peer-reviewed papers

Invited Talks:

• Ed Fox, Virginia Tech, USA: User Discovery and Exploration in Future Digital Libraries
• Tony Russell-Rose, 2Dsearch and Goldsmiths, University of London, UK: Searching, fast and slow
• Emanuele Di Buccio, University of Padua, Italy: Data Science and Information Access for Social Research on Technoscientific Issues in the Media
• Martin White, Intranet Focus Ltd and University of Sheffield, UK: Understanding and solving the complex IIR challenges of searching enterprise content
• Lorraine Goeuriot, Univ. Grenoble Alpes, France: Exploiting clinical data to build patients trajectories
• Tobias Eljasik-Swoboda et al, Fernuniversität Hagen, Germany: Querying by Example Using Bootstrapped Explainable Text Categorization in Emergent Knowledge-Domains
• Kevin Berwind, Fernuniversität Hagen, Germany: Design of use case diagrams and personas based on the CRISP4BigData process / Conceptual Design and Implementation of a graphical user interface for CRISP4BigData


Accepted Papers:

• Morshed Adnan, Matthias Hemmje and Michael Alexander Kaufmann. Social Media Mining to Study Social User Groups by Visualizing Tweet Clusters using Word2Vec, PCA and K-Means
• Mahmoud Artemi and Haiming Liu. A User Study on User's Attention for an Interactive Content-based Image Search System
• Stefan Wagenpfeil, Felix Engel, Paul McKevitt and Matthias Hemmje. Semantic Query Construction and Result Representation based on Graph Codes
• Nicholas Collis and Ingo Frommholz. AQUACOLD: A Novel Crowdsourced Linked Data Question Answering System
• Ghadeer Abuoda, Chad Hendrix and Stuart Campo. Automatic Tag Recommendation for the UN Humanitarian Data Exchange
• Thoralf Reis, Sebastian Bruchhaus, Binh Vu, Marco X. Bornschlegl and Matthias L. Hemmje. Towards Modeling AI-based User Empowerment for Visual Big Data Analysis