Visualizations for an Explainable Planning Agent

In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making. Imposing transparency and explainability requirements on such agents is especially important in order to establish trust and common ground with the end-to-end automated planning system. Visualizing the agent's internal decision-making processes is a crucial step towards achieving this. This may include externalizing the "brain" of the agent -- starting from its sensory inputs, to progressively higher order decisions made by it in order to drive its planning components. We also show how the planner can bootstrap on the latest techniques in explainable planning to cast plan visualization as a plan explanation problem, and thus provide concise model-based visualization of its plans. We demonstrate these functionalities in the context of the automated planning components of a smart assistant in an instrumented meeting space.Comment: PREVIOUSLY Mr. Jones -- Towards a Proactive Smart Room Orchestrator (appeared in AAAI 2017 Fall Symposium on Human-Agent Groups

Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201

Social media as an e-health communication channel: the use of (@medtweetmyhq) among students of UiTM Melaka / Wan Azfarozza Wan Athmar... [et al.]

Social media are now acknowledged as one of the platforms for engaging e-health that contributing to serious discussion and information regarding on medical and health issues. However, there are challenges and risks associated with social media in medical and health care which is misinformation. Misinformation can spread quickly on Twitter and each retweet is exposing to wider audiences. The aim of this paper is to identify the use of @MedTweetMYHQ among its’ users sepcifically among UiTM Melaka students. The researchers used in-depth interviews to five informants based on purposive sampling. The data was analysed using thematic analysis. Four themes emerged from the analysis which are the use of @MedTweetMYHQ to receive updated useful information on health, to share information on healthy lifestyle, to debunk health myths and as a platform for health discussion

A model for the integration of interactive visualizations into the process of information searching and linking on the Web

The Web provides access to a mass of heterogeneous information such as: websites, news, articles, statistics, numbers, facts and so on. Accessing this information through search engines and browsing is nowadays a standard procedure for everyone. Interactive visualizations are not yet an integral part of this search process due to a long-time lack of standards for native graphics on the Web and a lack of models for their connectivity. However, interactive visualizations provide a lot of benefits like (1) a variety of different representations for big, heterogeneous and complex information and (2) their interactivity that supports the cognition process of the user. In this article, a model for the integration of interactive visualizations into the process of information searching and linking on the Web is developed. This enables interactive visualizations to be an integral part of the web search process. The model has been used as basis for the implementation of the Vizgr toolkit and has been applied and tested in different application scenarios. This article is a shortened and revised summary of the relevant chapter in the dissertation of Hienert (2013)

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

Towards an extended festival viewing experience

Media coverage of large-scale live events is becoming increasingly complex, with technologies enabling the delivery of a broader range of content as well as complex viewing patterns across devices and services. This paper presents a study aimed at understanding the experience of people who have followed the broadcast coverage of a music festival. Our findings show that the experience takes a diversity of forms and bears a complex relationship with the actual experience of being at the festival. We conclude this analysis by proposing that novel services for coverage of this type of events should connect and interleave the diverse threads of experiences around large-scale live events and consider involving more diverse elements of the experience of “being there”

Towards an extended festival viewing experience

Media coverage of large-scale live events is becoming increasingly complex, with technologies enabling the delivery of a broader range of content as well as complex viewing patterns across devices and services. This paper presents a study aimed at understanding the experience of people who have followed the broadcast coverage of a music festival. Our findings show that the experience takes a diversity of forms and bears a complex relationship with the actual experience of being at the festival. We conclude this analysis by proposing that novel services for coverage of this type of events should connect and interleave the diverse threads of experiences around large-scale live events and consider involving more diverse elements of the experience of ``being there''

Real-time Event Detection on Social Data Streams

Social networks are quickly becoming the primary medium for discussing what is happening around real-world events. The information that is generated on social platforms like Twitter can produce rich data streams for immediate insights into ongoing matters and the conversations around them. To tackle the problem of event detection, we model events as a list of clusters of trending entities over time. We describe a real-time system for discovering events that is modular in design and novel in scale and speed: it applies clustering on a large stream with millions of entities per minute and produces a dynamically updated set of events. In order to assess clustering methodologies, we build an evaluation dataset derived from a snapshot of the full Twitter Firehose and propose novel metrics for measuring clustering quality. Through experiments and system profiling, we highlight key results from the offline and online pipelines. Finally, we visualize a high profile event on Twitter to show the importance of modeling the evolution of events, especially those detected from social data streams.Comment: Accepted as a full paper at KDD 2019 on April 29, 201