@article{ART003218148},
author={Jeong Do-heon and Gyuhwan Kim},
title={Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data},
journal={Journal of Korean Library and Information Science Society},
issn={2466-2542},
year={2025},
volume={56},
number={2},
pages={177-196}
TY - JOUR
AU - Jeong Do-heon
AU - Gyuhwan Kim
TI - Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data
JO - Journal of Korean Library and Information Science Society
PY - 2025
VL - 56
IS - 2
PB - Korean Library And Information Science Society
SP - 177
EP - 196
SN - 2466-2542
AB - This study aims to establish an automated analysis framework that quantitatively derives and visualizes latent movement path patterns within a public library, using real-time movement data collected through IoT-based camera sensors. To this end, continuous movement data captured by the sensors were structured using an N-gram approach and analyzed using Latent Dirichlet Allocation(LDA) topic modeling. Two term weighting methods—TF-IDF and Word2Vec—were each combined with bigram and trigram models, resulting in four analytical models. Topic distributions from each model were compared, and the structural characteristics of movement flows were visualized. To address the limitation of conventional LDA in capturing directionality and sequential information, the study also proposed an analysis method based on the Topical N-gram technique. The analysis results from each model were integrated using an ensemble approach based on cosine similarity and Jensen-Shannon Divergence (JSD). The experimental results revealed meaningful and repetitive movement patterns that are difficult to detect using simple statistical methods. In particular, key user routes centered around the ‘entrance’ and the ‘information desk’—both serving as guidance and reference service hubs—were clearly identified. This study is significant in that it presents an integrated analysis framework capable of quantitatively interpreting user behavior based on real-time movement data, offering practical applications for the operation and planning of public services.
KW - Movement Path Pattern;Internet of Things(IoT);LDA Topic Modeling;N-gram;Ensemble Method
DO -
UR -
ER -
Jeong Do-heon and Gyuhwan Kim. (2025). Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data. Journal of Korean Library and Information Science Society, 56(2), 177-196.
Jeong Do-heon and Gyuhwan Kim. 2025, "Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data", Journal of Korean Library and Information Science Society, vol.56, no.2 pp.177-196.
Jeong Do-heon, Gyuhwan Kim "Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data" Journal of Korean Library and Information Science Society 56.2 pp.177-196 (2025) : 177.
Jeong Do-heon, Gyuhwan Kim. Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data. 2025; 56(2), 177-196.
Jeong Do-heon and Gyuhwan Kim. "Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data" Journal of Korean Library and Information Science Society 56, no.2 (2025) : 177-196.
Jeong Do-heon; Gyuhwan Kim. Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data. Journal of Korean Library and Information Science Society, 56(2), 177-196.
Jeong Do-heon; Gyuhwan Kim. Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data. Journal of Korean Library and Information Science Society. 2025; 56(2) 177-196.
Jeong Do-heon, Gyuhwan Kim. Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data. 2025; 56(2), 177-196.
Jeong Do-heon and Gyuhwan Kim. "Analyzing Movement Path Patterns of Library Users Using a Topical N-gram Method Based on IoT Sensor Data" Journal of Korean Library and Information Science Society 56, no.2 (2025) : 177-196.
