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Section: New Results
Users Modeling and Designing Interaction
User-centered Heuristics for the Control of Personal Data
Participants : Patrice Pena, Alain Giboin.
This work is done in collaboration with Karima Boudaoud, SPARKS, I3S. In the context of the PadDOC FUI project, we elaborated a set of user-centered heuristics and a procedure for designing and evaluating systems allowing the control of personal data. The elaboration of the heuristics is based on: (1) the transposal of Nielsen’s heuristics and of Scapin and Bastien’s ergonomic criteria to the control of personal data ; (2) the user centering of the Privacy-by-Design notion of integrated privacy; and (3) the integration of Altman’s interaction approach to privacy [71].
User Modeling of Collaborative Ontology Editors/Environments
Participant : Alain Giboin.
To demonstrate the importance of an in-depth modeling of users in the design of collaborative ontologies editors or environments (COEs), we began a study on the evolution of the user modeling techniques and the resulting user models from the origins of the design of COEs.
Recommendation of Pedagogical Resources Adapted to User Profile and Context
Participants : Oscar Rodríguez Rocha, Catherine Faron-Zucker.
In the continuation of the Semantic Educloud project, we constructed an ontology and associated thesaurus to represent an official standard of knowledge and skills. We proposed a process to extract knowledge and skills from the official texts describing the French educational program and to automatically populate our ontology with the knowledge extracted from the official texts which we further enrich by aligning it with the Web of Data. This work has been presented at the EKM 2016 workshop [49].
Together with researchers from DUIN (Italy), we worked on the design of a recommendation algorithm based on Linked Data, that could be used to recommend pedagogical resources. The algorithm exploits existing relationships between resources by dynamically analyzing both the categories to which they belong to and their explicit references to other resources. The algorithm has been applied in a mobile application to recommend movies by relying on DBpedia. This work has been presented at the RecSys workshop [50]
Requirements Analysis
Participant : Isabelle Mirbel.
Requirements representation in agile methods is often done on the basis of User Stories (US) which are short sentences relating a WHO, WHAT and (possibly) WHY dimension. They are by nature very operational and simple to understand thus very efficient. Previous research allowed to build a unified model for US templates associating semantics to a set of keywords based on templates collected over the Web and scientific literature. Since the semantics associated to these keywords is mostly issued of the i* framework (http://www.cs.toronto.edu/km/istar/), we overviewed in this work how to build a custom rationale diagram on the basis of a US set tagged using that unified template. The rationale diagram is strictly speaking not an i* strategic rationale diagram but uses parts of its constructs and visual notation to build various trees of relating US elements in a single project. Indeed, the benefits of editing such a rationale diagram is to identify depending US, identifying EPIC ones (EPIC: large User Story) and group them around common Themes. The results of this research have been published in [51].
Design of a User-Centered Evaluation Method of Exploratory Search Systems Based on a Model of the Exploratory Search Process
Participants : Emilie Palagi, Alain Giboin, Fabien Gandon.
This work was undertaken in the context of the PhD of Emilie Palagi, in cooperation with with Raphaël Troncy (Eurecom). Our method takes into account users’s Exploratory Search (ES) behavior and will be based on a cognitive model of an ES task. We will specially work on Discovery Hub and 3cixty 4 (EURECOM project) ESSs.
During the first year of the PhD, we were looking for a model of ES process on which the method will be based. To achieve this objective, several models of information seeking process were analyzed and we compared them with our own grid of the typical characteristics of exploratory search activities. The chosen model will fill the grid as much as possible with suitable adaptations if needed. It is an on-going work and we are actually designing an ES search model. We also performed a comparative analysis of 15 ESSs in order to identify the relevant functionalities supporting an exploratory search. We want to associate these functionalities to our grid of exploratory search characteristics. We will select some of these systems to test and validate the future method.
Contrary to lookup search engines that help users to retrieve specific items (e.g., names, numbers, short statements, or specific documents), Exploratory Search Systems (ESSs) are search engines that help users to explore a topic of interest. ES tasks are open-ended, multi-faceted, and iterative like learning or topic investigation [77], [80]. Currently, the evaluation methods of ESSs are not entirely adapted to the special features of ES tasks, and do not effectively assess that ESSs support users in performing those tasks. Our research goal is to elaborate methods that effectively lead to this assessment.