Jae-min Cho

Large-scale Text-to-image Generation Models (LTGMs) (e.g., DALL-E), self-supervised deep learning models trained on a huge dataset, have demonstrated the capacity for generating high-quality open-domain images from multi-modal input. Although they can even produce anthropomorphized versions of objects and animals, combine irrelevant concepts in reasonable ways, and give variation to any user-provided images, we witnessed such rapid technological advancement left many visual artists disoriented i

In this paper, we introduce LiveGantt as a novel interactive schedule visualization tool that helps users explore highly-concurrent large schedules from various perspectives. Although a Gantt chart is the most common approach to illustrate schedules, currently available Gantt chart visualization tools suffer from limited scalability and lack of interactions. LiveGantt is built with newly designed algorithms and interactions to improve conventional charts with better scalability, explorability, a

We present a systematic review on three comparative layouts-juxtaposition, superposition, and explicit-encoding-which are information visualization (InfoVis) layouts designed to support comparison tasks. For the last decade, these layouts have served as fundamental idioms in designing many visualization systems. However, we found that the layouts have been used with inconsistent terms and confusion, and the lessons from previous studies are fragmented. The goal of our research is to distill the

Recent advancements in tablet technology pose a great opportunity for information visualization to expand its horizons beyond desktops. In this paper, we present TouchPivot, a novel interface that assists visual data exploration on tablet devices. With novices in mind, TouchPivot supports data transformations, such as pivoting and filtering, with simple pen and touch interactions, and facilitates understanding of the transformations through tight coupling between a data table and visualization.

This prospective study explored the relationship between expression of AKR1B10 mRNA and various clinical parameters in non-small-cell lung cancer (NSCLC) in terms of its validation as a marker for NSCLC. Tumour tissue samples were collected from 229 patients with NSCLC. Tissue samples from adjacent non-malignant lung tissue (> 5 cm from the tumour) of 89 of these patients and samples from 20 patients with benign lung disease were used as controls. Quantitative reverse transcription- polymerase c

Multiclass maps are scatterplots, multidimensional projections, or thematic geographic maps where data points have a categorical attribute in addition to two quantitative attributes. This categorical attribute is often rendered using shape or color, which does not scale when overplotting occurs. When the number of data points increases, multiclass maps must resort to data aggregation to remain readable. We present multiclass density maps: multiple 2D histograms computed for each of the category

We present Joint t-Stochastic Neighbor Embedding (Joint t-SNE), a technique to generate comparable projections of multiple high-dimensional datasets. Although t-SNE has been widely employed to visualize high-dimensional datasets from various domains, it is limited to projecting a single dataset. When a series of high-dimensional datasets, such as datasets changing over time, is projected independently using t-SNE, misaligned layouts are obtained. Even items with identical features across dataset

We present PANENE, a progressive algorithm for approximate nearest neighbor indexing and querying. Although the use of k-nearest neighbor (KNN) libraries is common in many data analysis methods, most KNN algorithms can only be queried when the whole dataset has been indexed, i.e., they are not online. Even the few online implementations are not progressive in the sense that the time to index incoming data is not bounded and cannot satisfy the latency requirements of progressive systems. This lon

Usage patterns of mobile devices depend on a variety of factors such as time, location, and previous actions. Hence, context-awareness can be the key to make mobile systems to become personalized and situation dependent in managing their resources. We first reveal new findings from our own Android user experiment: (i) the launching probabilities of applications follow Zipf's law, and (ii) inter-running and running times of applications conform to log-normal distributions. We also find context-de

We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster reliability of multidimensional projection (MDP), specifically how well the inter-cluster structures are preserved between the original high-dimensional space and the low-dimensional projection space. Measuring inter-cluster reliability is crucial as it directly affects how well inter-cluster tasks (e.g., identifying cluster relationships in the original space from a projected view) can be conducted; however,

Wordle has been commonly used to summarize texts, with each word size-coded by its frequency of occurrences--the more often a word occurs in texts, the bigger it is. The interactive authoring tool WordlePlus leverages natural interaction and animation to give users more control over wordle development. WordlePlus supports direct manipulation of words with pen and touch interaction. It introduces two-word multitouch manipulation, such as concatenating and grouping two words, and provides pen inte

We present a progressive algorithm for approximate k-nearest neighbor search. Although the use of k-nearest neighbor libraries (KNN) is common in many data analysis methods, most KNN algorithms can only be run when the whole dataset has been indexed, i.e., they are not online. Even the few online implementations are not progressive in the sense that the time to index incoming data is not bounded and can exceed the latency required by progressive systems. This latency significantly restricts the