22 March 2022, Virtual
Submission deadline: January 3, 2022 (midnight Hawaii time)
Acceptance notification: January 28, 2022
Final manuscript due: February 11, 2022
Workshop: March 22, 2022
This workshop will be part of the ACM Intelligent User Interfaces 2022 Conference (http://iui.acm.org/2022/). The workshop focuses on systems that personalize, summarize and visualize data for supporting interactive information seeking and information discovery, along with tools that enable user modeling and methods for incorporating user needs and preferences into both analytics and visualization. Additionally, exploratory search is an important tool in how people interact with algorithms online. Examples for interacting with online algorithms are recommender systems, and the understanding of online manipulation systems and algorithms, including bots and the promotion of fake news.
Our aim is to bring together researchers and practitioners working on different personalization aspects and applications of exploratory search and interactive data analytics. This will allow us to achieve four goals: (1) propose new strategies for systems that need to convey the rationale behind their decisions or inference, and the sequence of steps that lead to speciﬁc (search) results; (2) develop new user modeling and personalization techniques for exploratory search and interactive data analytics; (3) develop design principles for exploratory search of online algorithms and systems; (4) develop a set of evaluation metrics for personalization in exploratory search. The workshop aims to solicit submissions in the following areas of personalized interactive data analytics and exploratory search:
Personalized interactive exploration via interactive data analytics:
– personalization aspects in systems for exploratory search.
– cross-domain/ context-aware/ cross-platform exploratory search systems.
– interactive interfaces for data-intensive platforms.
– preprocessing vs. online processing.
– interactive data visualization
– evaluation of human-centered exploratory search and data analytics.
Explainable intelligent systems:
– metrics for explainable exploratory search.
– explainability and transparency in expert vs. non-expert systems.
– human-in-the-loop analytics systems.
– efﬁcient vs. explainable analytics.
– user perception of explainability and transparency in interactive intelligent systems.
Interaction with Online algorithms
– conveying awareness of algorithmic fairness and bias in retrieval systems.
– exploratory studies of online algorithms and recommender systems.
– exploratory search of online manipulation systems and algorithms (e.g., fake news and bots).
– interactively modelling user’s information needs for high-recall information retrieval.
– new applications of exploratory search and interactive data analytics.
Department of Computer Science, University of Helsinki (Finland), glowacka[at]cs.heelsinki.fi
Faculty of Computer Science, Dalhousie University (Canada), eem[at]cs.dal.ca
Axel J. Soto,
Institute for Computer Science and Engineering, UNS - CONICET (Argentina), axel.soto[at]cs.uns.edu.ar
Fernando V. Paulovich,
Faculty of Computer Science, Dalhousie University (Canada), paulovich[at]dal.ca
Osnat (Ossi) Mokryn,
Department of Information Systems, University of Haifa (Israel), omokryn[at]univ.haifa.ac.il
We encourage submissions of work in progress, concept papers, case studies, ongoing research projects, reports on recently completed PhD dissertations or recently accepted journal papers, and generally material that will stimulate discussion, generate useful feedback to the authors, encourage research collaborations and vigorous exchange of ideas on promising research directions.
The length should be less than 5000 words and it should follow IUI's formatting guidelines
Papers can be submitted through EasyChair:
Osnat (Ossi) Mokryn Information Systems University of Haifa http://scan.haifa.ac.il -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 17931 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20211102/74435ec8/attachment.txt>