Tak Yeon Lee

University of Maryland, College Park | UMD, UMCP, University of Maryland College Park · Department of Computer Science

An increasing number of web articles engage the reader with the feeling of being immersed in the data space. However, the exact characteristics of spatial immersion in the context of visual storytelling remain vague. For example, what are the common design patterns of data stories with spatial immersion? How do they affect the reader's experience?...

In this work, we research user preferences to see a chart, table, or text given a question asked by the user. This enables us to understand when it is best to show a chart, table, or text to the user for the specific question. For this, we conduct a user study where users are shown a question and asked what they would prefer to see and used the dat...

Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset, and not the actual user and their past visualization feedback. These systems recommend the same visualizations for every user, despite that the underlying user interests, intent, and visualization preferences are likely to be fundamentall...

Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualizati...

Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualizati...

Visualization recommendation systems simplify exploratory data analysis (EDA) and make understanding data more accessible to users of all skill levels by automatically generating visualizations for users to explore. However, most existing visualization recommendation systems focus on ranking all visualizations into a single list or set of groups ba...

Visualization recommendation seeks to generate, score, and recommend to users useful visualizations automatically, and are fundamentally important for exploring and gaining insights into a new or existing dataset quickly. In this work, we propose the first end-to-end ML-based visualization recommendation system that takes as input a large corpus of...

Links and their landing pages in the World Wide Web are oftentimes flawed or irrelevant. We created a data set of 4266 links within 160 marketing emails whose relevance with landing pages have been evaluated by crowd workers. We present a study of common misalignments and propose methods for detecting these misalignments. An F-score of 0.63 can be...

A key requirement of successful online marketing is to maintain the quality of hyperlinks. However, it is not uncommon for users to get confused or disappointed by a wide range of misalignments between links and their landing pages. This paper presents an online survey that identifies types of such misalignments perceived by recipients.

Probabilistic topic models are important tools for indexing, summarizing, and analyzing large document collections by their themes. However, promoting end-user understanding of topics remains an open research problem. We compare labels generated by users given four topic visualization techniques—word lists, word lists with bars, word clouds, and ne...

Programming-by-Example (PBE) enables users to create programs without writing a line of code. However, there is little research on people's ability to accomplish complex tasks by providing examples, which is the key to successful PBE solutions. This paper presents an online user study, which reports observations on how well people decompose complex...

Topic modeling is a common tool for understanding large bodies of text, but is typically provided as a “take it or leave it” proposition. Incorporating human knowledge in unsupervised learning is a promising approach to create high-quality topic models. Existing interactive systems and modeling algorithms support a wide range of refinement operatio...

End-user programming (EUP) is a common approach for helping ordinary people create small programs for their professional or daily tasks. Since end-users may not have programming skills or strong motivation for learning them, tools should provide what end-users want with minimal costs of learning –i.e., they must decrease the barriers to entry. Howe...

We believe that children as young as ten can directly benefit from opportunities to engage in computational thinking. One approach to provide these opportunities is to focus on social game play. Understanding game play is common across a range of media and ages. Children can begin by solving puzzles on paper, continue on game boards, and ultimately...

This paper examines the relationship between motivational design and its longitudinal effects on crowdsourcing systems. In the context of a company internal web site that crowdsources the identification of Twitter accounts owned by company employees, we designed and investigated the effects of various motivational features including individual / so...

Effective online display advertising requires a dynamic se-lection of the advertisement to be displayed when a web page is fetched. As the goal of displaying advertisement is to engage the users and obtain clicks, the advertisement which has the highest probability of click should be dis-played. In this paper we address the problem of finding the m...

In this paper we describe CTArcade, a web application framework that seeks to engage users through game play resulting in the improvement of computational thinking (CT) skills. Our formative study indicates that CT skills are employed when children are asked to define strategies of common games such as Connect Four. In CTArcade, users can train the...

The American Recovery and Reinvestment Act dedicated $787 billion to stimulate the US economy and mandated the release of the data describing the exact distribution of that money. The dataset is a large and complex one; one of its distinguishing features is its bi-hierarchical structure, arising from the distribution of money through agencies to sp...