∙ GameBot: A Visualization-augmented Chatbot for Sports Game
CHI’20 Extended Abstracts, CHI Conference on Human Factors in Computing
The major sports leagues, including The National Basket- ball Association (NBA) and the EPL (the English Premier League), are adopting conversational systems (chatbots) as an innovative outlet to deliver game information and engage fans. However, current sports chatbots only provide scores and game highlight videos, which are often inadequate for statistical data related requests. We present GameBot, an interactive chatbot for sports fans to explore game statisti- cal data. GameBot features (1) the direct answers to user’s stats-related questions, and (2) the use of data visualiza- tions as supporting context for sports fans’ stats-related questions.
pdf I preview video
∙ Visual Dashboard Design for eSports Spectatorship: Opportunities and Challenges
SEEGames’20 workshop, CHI Conference on Human Factors in Computing
Spectatorship is an integral part of the massively popular eSports due to its spectator-friendly nature. Previous research has examined eSports fans’ spectator motivation and the role of technology in supporting and enriching fans’ spectator experience for eSports and traditional sports as well. Inspired by this work, we discuss the opportunities and challenges of three future directions on designing a visual dashboard for eSports spectatorship.
∙ Linking and Layout: Exploring the Integration of Text and Visualization in Storytelling
21st EG/VGTC Conference on Visualization (EuroVis’19)
We seek to understand two text visualization integration forms: (i) different text and visualization spatial arrangements (layout), namely, vertical and slideshow; and (ii) interactive linking of text and visualization (linking). Through a crowdsourced study with 180 participants, we measured the effect of layout and linking on the degree to which users engage with the story (user engagement), their understanding of the story content (comprehension), and their ability to recall the story information (recall).
I study website I preview video
∙ GameViews: Understanding and Supporting Data-driven Sports Storytelling
CHI’19 honorable mention, top 5% of all the papers
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
In this paper, we explore how these stakeholders construct data-driven sports stories. we implemented two exploratory prototypes: GameViews-Writers for sportswriters to quickly extract key game information and GameViews-Fans to support a real-time data-driven game- viewing experience for fans. We report insights from two user studies conducted with four professional sportswriters and eight sports fans, respectively.
pdf I slides I preview video I video I GameViews-Writers Demo
∙ VisPod: Content-Based Audio Visual Navigation
23rd International Conference on Intelligent User Interfaces (IUI'18) demo
We present VisPod, a visual audio player that visually displays the main topics and keywords extracted from the transcript. VisPod supports (1) audio content browsing, (2) topic-based and keyword-based navigation, (3) communication of transcript and speaker information in real time, and (4) content-based query.
pdf I Video I Demo
∙ Coupling Story to Visualization: Using Textual Analysis as a Bridge Between Data and Interpretation
23rd International Conference on Intelligent User Interfaces (IUI'18)
We propose an approach to automatically integrate text and vi- sualization elements. We leverage natural language processing, quantitative narrative analysis, and information visualization to (1) automatically extract narrative components (who, what, when, where) from data-rich stories, and (2) integrate the supporting data evidence with the text to develop a narrative visualization.
pdf I slides I Video I Demo
∙ Recognizing Handwritten Source Code
Proceedings of Graphics Interface 2017 (GI'17)
we explore handwriting recognition for source code. We collect and make publicly available a dataset of handwritten Python code samples from 15 participants. We present an approach to improve the recognition accuracy by aug- menting a handwriting recognizer with the programming language grammar rules. Our experiment on the collected dataset shows an 8.6% word error rate and a 3.6% character error rate which outperforms standard handwriting recognition systems and compares favorably to typing source code on virtual keyboards.
PDF I Slides I Website
∙ Docio: Documenting API Input/Output Examples
Proceedings of the 25th IEEE International Conference on Program Comprehension, Tool Demo Track (ICPC'17)
We demonstrate a prototype toolset we built to generate I/O examples. our tool logs I/O values when API functions are executed, for example in running test suites. Then, our tool puts I/O values into API documents as I/O examples. our tool has three programs: 1) funcWatch, which collects I/O values when API developers run test suites, 2) ioSelect, which selects one I/O example from a set of I/O values, and 3) ioPresent, which embeds the I/O examples into documents.
∙ An combined sentiment classification system for SIGHAN-8
Eighth SIGHAN Workshop on Chinese Language Processing at the Association for Computational Linguistics (ACL-IJCNLP'15)
This paper describes our system (MSIIP THU) used for Topic-Based Chinese Message Polarity Classification Task in SIGHAN-8. In our system, a lexiconbased classifier and a statistical machine learning-based classifier are built up, followed by a linear combination of these two models. The overall performance of the proposed framework ranks in the middle of all terms participating in the task.