Interactive Visual Facets to Support Fluid Exploratory Search

Exploratory search starts with ill-defined goals and involves browsing, learning, and formulating new targets for search. To fluidly support such dynamic search behaviours, we focus on devising interactive visual facets (IVF), visualising information facets to support user comprehension and control of the information space. To do this, we reviewed existing faceted search interfaces and derived two design requirements (DR) that have not been fully addressed to sup- port fluid interactions in exploratory search. We then exemplified the requirements through devising an IVF tool, which coordinates a linear and a categorical facet representing the distribution and summarisation of items, respectively, and providing context for faceted exploration (DR1). To support rapid transitions between search criteria (DR2), the tool introduces a novel design concept of using facets to select items without filtering the item space. Particularly, we propose a filter-swipe technique that enables users to drag a categorical facet value sequentially over linear facet bars to view the items in the intersection of the two facets along with the categorical facet dynamically summarizing the items in the interaction. A user study of 11 participants with realistic email search tasks shows that dynamic suggestions through the timeline navigation can help discover useful suggestions for search; the novel design concept was favoured over using facet values as filters. Based on these practices, we derive IVF design implications for fluid, exploratory searches.Peer reviewe

Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge

Motivation: Precision medicine requires the ability to predict the efficacies of different treatments for a given individual using high-dimensional genomic measurements. However, identifying predictive features remains a challenge when the sample size is small. Incorporating expert knowledge offers a promising approach to improve predictions, but collecting such knowledge is laborious if the number of candidate features is very large. Results: We introduce a probabilistic framework to incorporate expert feedback about the impact of genomic measurements on the outcome of interest and present a novel approach to collect the feedback efficiently, based on Bayesian experimental design. The new approach outperformed other recent alternatives in two medical applications: prediction of metabolic traits and prediction of sensitivity of cancer cells to different drugs, both using genomic features as predictors. Furthermore, the intelligent approach to collect feedback reduced the workload of the expert to approximately 11%, compared to a baseline approach.Peer reviewe

Designing for Engagement: Using indirect manipulation to support form exploration in 3D modeling

This thesis aims to study the design possibilities for supporting explorative form-finding in 3D modeling applications. For today’s many design professions, 3D forms are achieved partly in engagement with digital environments. Use of software has far exceeded final idea execution, extending to the early phases of design work in which the outcome is not predetermined. This insight led designers of interactive systems support sketching and ideating activities by reducing the risk of experimentation and cognitive effort demanded from user. Yet, there has been less emphasis on traditional design and craft practice that acknowledges engagement with materials and effort spent on work as an integral part of creative process.The notion of exploration in the scope of this thesis attempts to incorporate such aspects. Relevant literature about workshop practice in design and craft has been reviewed, as well as examples of CAD technologies that aid designers. In this light, HCI perspectives on the design of creativity support tools and games have been discussed. The thesis work aimed to concretize this background by building a design strategy and an interactive artifact. A 3D form-finding application concept using objects in modeling space to indirectly manipulate geometry, “kfields”, has been developed and evaluated with users at various stages. The thesis concludes by reflecting on the findings of different design stages and proposing further directions for design

Designing for Engagement: Using indirect manipulation to support form exploration in 3D modeling

This thesis aims to study the design possibilities for supporting explorative form-finding in 3D modeling applications. For today’s many design professions, 3D forms are achieved partly in engagement with digital environments. Use of software has far exceeded final idea execution, extending to the early phases of design work in which the outcome is not predetermined. This insight led designers of interactive systems support sketching and ideating activities by reducing the risk of experimentation and cognitive effort demanded from user. Yet, there has been less emphasis on traditional design and craft practice that acknowledges engagement with materials and effort spent on work as an integral part of creative process.The notion of exploration in the scope of this thesis attempts to incorporate such aspects. Relevant literature about workshop practice in design and craft has been reviewed, as well as examples of CAD technologies that aid designers. In this light, HCI perspectives on the design of creativity support tools and games have been discussed. The thesis work aimed to concretize this background by building a design strategy and an interactive artifact. A 3D form-finding application concept using objects in modeling space to indirectly manipulate geometry, “kfields”, has been developed and evaluated with users at various stages. The thesis concludes by reflecting on the findings of different design stages and proposing further directions for design

Zhodnocení chovu australského ovčáka v ČR

We present the design and implementation of mailVis, an interactive visual interface for email boxes that facilitates re-finding of emails. Email re-finding tasks can be challenging, involving scanning of many emails and modifying the query as the search progresses. We designed mailVis for such tasks in which the user would benefit from having memory clues and multiple options to direct the search. During the design process, we devised a novel interaction technique, filter swipe, that combines filtering and selection into one action for rapidly skimming individual items in a data set

Integrating neurophysiologic relevance feedback in intent modeling for information retrieval

The use of implicit relevance feedback from neurophysiology could deliver effortless information retrieval. However, both computing neurophysiologic responses and retrieving documents are characterized by uncertainty because of noisy signals and incomplete or inconsistent representations of the data. We present the first-of-its-kind, fully integrated information retrieval system that makes use of online implicit relevance feedback generated from brain activity as measured through electroencephalography (EEG), and eye movements. The findings of the evaluation experiment (N = 16) show that we are able to compute online neurophysiology-based relevance feedback with performance significantly better than chance in complex data domains and realistic search tasks. We contribute by demonstrating how to integrate in interactive intent modeling this inherently noisy implicit relevance feedback combined with scarce explicit feedback. Although experimental measures of task performance did not allow us to demonstrate how the classification outcomes translated into search task performance, the experiment proved that our approach is able to generate relevance feedback from brain signals and eye movements in a realistic scenario, thus providing promising implications for future work in neuroadaptive information retrieval (IR).Peer reviewe

Developing a Symbiotic System for Scientific Information Seeking: The Mindsee Project

This paper describes an approach for improving the current systems supporting the exploration and research of scientific literature, which generally adopt a query-based information-seeking paradigm. Our approach is to use a symbiotic system paradigm, exploiting central and peripheral physiological data along with eye-tracking data to adapt to users' ongoing subjective relevance and satisfaction with search results. The system described, along with the interdisciplinary theoretical work underpinning it, could serve as a stepping stone for the development and diffusion of next-generation symbiotic systems, enabling a productive interdependence between humans and machines. After introducing the concept and evidence informing the development of symbiotic systems over a wide range of application domains, we describe the rationale of the MindSee project, emphasizing its BCI component and pinpointing the criteria around which users' evaluations can gravitate. We conclude by summarizing the main contribution that MindSee is expected to mak