WORKSHOP TOPIC AND DESCRIPTION

The workshop focuses on systems that personalize, summarize and visualize the data for supporting interactive information seeking and information discovery, along with tools that enable user modeling and methods for incorporating the user needs and preferences into both analytics and visualization. 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 a common set of design principles for this type of systems across platforms, contexts, users and applications; (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:

WORKSHOP TARGET AREAS
Personalized interactive exploration via interactive data analytics:
– personalization aspects in systems for exploratory search.
– cross-domain/ context-aware/ cross-platform exploratory search systems.
– interactively modelling the user’s information needs for high-recall information retrieval.
– new applications of exploratory search and interactive data analytics.

Data analytics:
– interactive interfaces for data-intensive platforms.
– interaction degrees of freedom.
– preprocessing vs. online processing.
– interactive data visualization evaluation of interactive systems for exploratory search and data analytics.

Metrics for 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.

Submission Information:

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, in one of the following formats:

- full papers (up to 8 pages in ACM sigconf format), which will presented either as contributed talks or posters

- extended abstracts (up to 4 pages in ACM sigconf format), which will be presented as posters with a possibility to be accompanied by a demo.

Papers can be submitted through EasyChair:

https://easychair.org/conferences/?conf=esida21