Myeong Lee

Information Science

Machine Learning

Identifying Urban Neighborhood Names through User-contributed Online Property Listings

Neighborhoods are vaguely defined, localized regions that share similar characteristics. They are most often defined, delineated, and named by the citizens that inhabit them rather than municipal government or commercial agencies. The names of these neighborhoods play an important role as a basis for community and sociodemographic identity, geographic communication, and historical context.

Making Information Deserts Visible: Computational Models, Disparities in Civic Technology Use, and Urban Decision Making

This research will develop a foundational tool for understanding how civic technologies are used and how information inequalities manifest in a city. User data from new civic technologies that reveal inequalities in the information environments of citizens has only recently become available. Since a large portion of data is demographically or geospatially biased due to varying human-data relationships, computational social scientists have used data modeling and algorithmic techniques to adjust the data and remove biases during data-processing.

Cycle Atlanta: Seeing Like a Bike

The Cycle Atlanta project aims at creating sensor systems that allow a bike to "see" its environment and collect data as a participatory effort so that we can help the City of Atlanta to make informed decisions about biking infrastructures. Specifically, a sensor box equipped with sonars, lidars, PM sensors, gas sensors, gyroscope, accelerometer, and others was developed to detect environmental factors that can give rise to cyclists' stress level. I participated in this project as a Data Science for Social Good (Atlanta's DSSG) Summer fellow in 2017.

A Tool for Estimating and Visualizing Poverty Maps

"Poverty maps" are designed to simultaneously display the spatial distribution of welfare and different dimensions of poverty determinants. The plotting of such information on maps heavily relies on data that is collected through infrequent national household surveys and censuses. However, due to the high cost associated with this type of data collection process, poverty maps are often inaccurate in capturing the current deprivation status.

Toward an Ecology Theory of Creativity in IT Products: A Study of Mobile Device Industry

In a creative process, divergent thinking needs to be stimulated to generate novel ideas; yet these ideas must be synthesized to produce something valuable. Hence to foster creativity in developing IT products, creators need to manage the tension between novelty and value. Since the forces affecting the novelty-value tension often exist outside a creator's group or organization, we apply organizational ecology theory to propose an industry-level, ecological model for understanding the novelty of IT products.

Image Retrieval Systems based on Color Similarity and Edge Detection

This project was conducted in 2008 for my bachelor's thesis in the Department of Electrical Engineering at Seoul National University (it was more like a capstone project rather than a thesis, since the focus of the project was mainly at implementing algorithms rather than analyzing the performance of algorithms using concrete measures, e.g., recall and precision). I implemented an image retrieval system prototype that takes an image as input, and outputs most similar images from the image database.

This Is Not Just a Café: Toward Capturing the Dynamics of Urban Places

Social media has provided a huge amount of user-generated data in capturing urban dynamics. Among them, place-level human behavior has been largely detected through people’s check-in records at certain places. Conventionally, places are characterized by a set of pre-defined features, often specified by the owner of the places. In this paper, we argue that capturing socially-meaningful features and dynamics of an urban place may also be done by analyzing human activity traces.

On Information Deserts

Information accessibility problems include diverse types of human- and system-driven barriers that make it difficult for individuals to access desired information. These issues have been studied in two main streams: (1) a human-centered view based on the understand­ing of individual-level characteristics such as physical impairment and economic status, and (2) a technology-focused view that emphasizes system-based factors such as the information filtering techniques and interface designs.

Large-scale News Image Analysis with MapReduce-based LSH and VisualRank

Hao Li (Ph.D. student from CS) and I conducted a big-data analysis project using the MapReduce framework (Hadoop) for the final project of INFM718G (Data-Intensive Computing with MapReduce, by Dr. Jimmy Lin). Targeting all the news images in April 2013, we tried to rank news images based on the importance and popularity level of each news image. To do that, we extracted image features using SIFT (Scale-invariant feature transform) and constructed a graph of images using LSH (Locality-sensitive Hashing) as a means to approximate the similarity of images.