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@inproceedings{10.1145/3486635.3491070,
author = {Li, Zekun and Guan, Runyu and Yu, Qianmu and Chiang, Yao-Yi and Knoblock, Craig A.},
title = {Synthetic Map Generation to Provide Unlimited Training Data for Historical Map Text Detection},
year = {2021},
isbn = {9781450391207},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3486635.3491070},
doi = {10.1145/3486635.3491070},
booktitle = {Proceedings of the 4th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery},
pages = {17–26},
numpages = {10},
keywords = {synthetic data generation, text detection, historical maps, datasets},
location = {Beijing, China},
series = {GEOAI '21}
}
@inproceedings{Modad22,
author = {Bassel Abou Ali Modad and Xin Yu and Hae Jin Song and Yao-Yi Chiang and Andreas Molisch},
title = {Cell-by-Cell Line-of-Sight Probability Models Based on Real-World Base Station Deployment},
year = {2022},
publisher = {IEEE},
booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
location = {Rio de Janeiro, Brazil}
}
@inproceedings{duan2021label,
title={A Label Correction Algorithm Using Prior Information for Automatic and Accurate Geospatial Object Recognition},
author={Duan, Weiwei and Chiang, Yao-Yi and Leyk, Stefan and Uhl, Johannes H and Knoblock, Craig A},
booktitle={2021 IEEE International Conference on Big Data (Big Data)},
pages={1604--1610},
year={2021},
organization={IEEE}
}
@inproceedings{10.1145/3474717.3486811,
author = {Jiao, Yuankun and Chiang, Yao-Yi},
title = {SRC: Incorporating Geographic Information for Building a Location-Based Recommendation System},
year = {2021},
isbn = {9781450386647},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3474717.3486811},
doi = {10.1145/3474717.3486811},
abstract = {This study proposes a novel approach for location recommendation based on content-based recommendation algorithms incorporated with geographic information. The study also analyzes the impact of various dimension reduction (DR) methods on the recommendation quality using various baseline approaches. The experiment demonstrates that the proposed approach to content-based location recommendations is feasible and valuable, with potentials for further research.},
booktitle = {Proceedings of the 29th International Conference on Advances in Geographic Information Systems},
pages = {680–681},
numpages = {2},
keywords = {dimension reduction, data mining, location recommendation system},
location = {Beijing, China},
series = {SIGSPATIAL '21}
}
@INPROCEEDINGS{hu22, author={Hu, H. and Lin, H. and Chiang, Y.-Y. }, booktitle={2022 IEEE International Conference on Big Data (Big Data)}, title={Clustering Human Mobility with Multiple Spaces}, year={2022}, volume={}, number={}, pages={}, doi={}}
@inproceedings{min22,
author = {Namgung, Min and Chiang, Yao-Yi },
title = {Incorporating Spatial Context for Post-OCR in Map Images},
year = {2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
booktitle = {Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery},
series = {GEOAI '22}
}
@INPROCEEDINGS{9671875, author={Duan, Weiwei and Chiang, Yao-Yi and Leyk, Stefan and Uhl, Johannes H. and Knoblock, Craig A.}, booktitle={2021 IEEE International Conference on Big Data (Big Data)}, title={Guided Generative Models using Weak Supervision for Detecting Object Spatial Arrangement in Overhead Images}, year={2021}, volume={}, number={}, pages={725-734}, doi={10.1109/BigData52589.2021.9671875}}
@INPROCEEDINGS{lin22, author={Lin, Y. and Chiang, Y.-Y. }, booktitle={2022 IEEE International Conference on Big Data (Big Data)}, title={A Semi-Supervised Learning Approach for Abnormal Event Prediction on Large Network Operation Time-Series Data}, year={2022}, volume={}, number={}, pages={}, doi={}}
@inproceedings{li22,
author = {Li, Z. and Kim, J. and Chiang, Y.-Y. and Chen, M.},
title = {SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity Representation},
year = {2022},
booktitle = {the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP) - Findings},
location = {Abu Dhabi}
}
@article{https://doi.org/10.1111/tgis.12975,
author = {Gao, Yuan and Chiang, Yao-Yi and Zhang, Xiaoxi and Zhang, Min},
title = {Traffic volume prediction for scenic spots based on multi-source and heterogeneous data},
journal = {Transactions in GIS},
volume = {26},
number = {6},
pages = {2415-2439},
doi = {https://doi.org/10.1111/tgis.12975},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/tgis.12975},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/tgis.12975},
abstract = {Abstract Traffic prediction for scenic spots is an important topic in modeling an urban traffic system. Existing traffic prediction approaches typically use raw traffic data and road networks without considering the physical environment and human–environment interaction. This article presents a novel traffic prediction model that considers: (1) the topological structure of the city road network; (2) the popularity and accessibility of each scenic spot in the city; and (3) the traffic volumes of nearby scenic spots. The proposed model first learns a series of traffic dependency graphs by the Multi-graph Convolutional Network using multiple data sources describing historical traffic volumes, scenic spots popularity, land function, location, and accessibility. The graph nodes represent the scenic spots, and the links between them represent their traffic dependency, considering all traffic and geographic features. Then the proposed model uses the Gated Recurrent Unit (GRU) to capture the temporal dependency between multiple fused graphs for traffic volume prediction. The experiments show that the proposed model (M-GCNGRU) can effectively exploit and integrate geographic data with historical traffic data for traffic volume prediction, outperforming several classical and state-of-the-art methods.},
year = {2022}
}
@article{shbita2022building,
title={Building Spatio-Temporal Knowledge Graphs from Vectorized Topographic Historical Maps},
author={Shbita, Basel and Knoblock, Craig A and Duan, Weiwei and Chiang, Yao-Yi and Uhl, Johannes H and Leyk, Stefan},
journal={Semantic Web},
number={Preprint},
pages={1--23},
year={2022},
publisher={IOS Press},
urlLink={https://content.iospress.com/articles/semantic-web/sw222918}
}
@ARTICLE{9924526, author={Zhang, Ying and Li, Muyang and Chen, Yuanchang and Chiang, Yao-Yi and Hua, Yunpeng}, journal={IEEE Transactions on Smart Grid}, title={A Constraint-based Routing and Charging Methodology for Battery Electric Vehicles with Deep Reinforcement Learning}, year={2022}, volume={}, number={}, pages={1-1}, doi={10.1109/TSG.2022.3214680}}
@ARTICLE{Gil2021-va,
title = "{Artificial Intelligence for Modeling Complex Systems: Taming the
Complexity of Expert Models to Improve Decision Making}",
author = "Gil, Yolanda and Garijo, Daniel and Khider, Deborah and
Knoblock, Craig A and Ratnakar, Varun and Osorio, Maximiliano
and Vargas, Hern{\'a}n and Pham, Minh and Pujara, Jay and
Shbita, Basel and Vu, Binh and Chiang, Yao-Yi and Feldman, Dan
and Lin, Yijun and Song, Hayley and Kumar, Vipin and Khandelwal,
Ankush and Steinbach, Michael and Tayal, Kshitij and Xu,
Shaoming and Pierce, Suzanne A and Pearson, Lissa and
Hardesty-Lewis, Daniel and Deelman, Ewa and Silva, Rafael
Ferreira Da and Mayani, Rajiv and Kemanian, Armen R and Shi,
Yuning and Leonard, Lorne and Peckham, Scott and Stoica, Maria
and Cobourn, Kelly and Zhang, Zeya and Duffy, Christopher and
Shu, Lele",
journal = "ACM Trans. Interact. Intell. Syst.",
publisher = "Association for Computing Machinery",
volume = 11,
number = 2,
pages = "1--49",
month = jul,
year = 2021,
url = "https://doi.org/10.1145/3453172",
file = "yaoyichi.github.io/papers-all//Gil-et-al.-2021-Artificial-Intelligence-for-Modeling-Complex-Systems-Taming-the-Complexity-of-Expert-Models-to-Improve-Decision-Making.pdf",
address = "New York, NY, USA",
issn = "2160-6455",
doi = "10.1145/3453172"
}
@INPROCEEDINGS{Avelar21-icc,
title = "{Measuring Closest Water, Sanitation, and Hygiene Facilities in Unhoused Communities of Los Angeles}",
booktitle = "{{Proceedings of the 30th International Cartographic Conference
(ICC'21)}}",
author = "Avelar Portillo, L. J. and Park, L. and Ko, C. and Vasquez, A. and Franklin, M. and Chiang, Y.-Y. ",
year = 2021
}
@INPROCEEDINGS{Feldman-rcv,
title = "{Enabling Responsible Computer Vision with FAIR Knowledge Graphs}",
booktitle = "{{Responsible Computer Vision, Conference on Computer Vision and Pattern Recognition 2021 Workshop}}",
author = "Feldman, D. and Chiang, Y.-Y. ",
year = 2021
}
@INPROCEEDINGS{Park21-icc,
title = "{Reimagining Measures of Spatial Access to Health Care in Low- And Middle-Income Countries: Using Road Network Analysis to Validate Self-Reported Perceptions of Geospatial Barriers}",
booktitle = "{{Proceedings of the 30th International Cartographic Conference
(ICC'21)}}",
author = "Park, L. and Birdwell, A. and Chiang, Y.-Y. ",
year = 2021
}
@INPROCEEDINGS{Avelar21-aag,
title = "{Impacts of COVID-19 on Water, Sanitation, and Hygiene (WaSH) Access in Skid Row, Los Angeles}",
booktitle = "{American Association of Geographers Annual Meeting}",
author = "Avelar Portillo, L. J. and Chiang, Y.-Y. and Franklin, M. and Ko, C. and Vasquez, A. ",
year = 2021
}
@ARTICLE{Zhang2021-ju,
title = "{BiS4EV: A fast routing algorithm considering charging stations and
preferences for electric vehicles}",
author = "Zhang, Ying and Wu, Bin and Chiang, Yao-Yi and Zhang, Xin and
Chen, Yuanchang and Li, Muyang and Li, Fanyu",
journal = "Engineering applications of artificial intelligence",
volume = 104,
pages = "104378",
month = sep,
year = 2021,
url = "https://www.sciencedirect.com/science/article/pii/S0952197621002268",
issn = "0952-1976",
doi = "10.1016/j.engappai.2021.104378"
}
@Article{s21175801,
AUTHOR = {Li, Kenan and Deng, Huiyu and Morrison, John and Habre, Rima and Franklin, Meredith and Chiang, Yao-Yi and Sward, Katherine and Gilliland, Frank D. and Ambite, José Luis and Eckel, Sandrah P.},
TITLE = {W-TSS: A Wavelet-Based Algorithm for Discovering Time Series Shapelets},
JOURNAL = {Sensors},
VOLUME = {21},
YEAR = {2021},
NUMBER = {17},
ARTICLE-NUMBER = {5801},
URL = {https://www.mdpi.com/1424-8220/21/17/5801},
PubMedID = {34502692},
ISSN = {1424-8220},
ABSTRACT = {Many approaches to time series classification rely on machine learning methods. However, there is growing interest in going beyond black box prediction models to understand discriminatory features of the time series and their associations with outcomes. One promising method is time-series shapelets (TSS), which identifies maximally discriminative subsequences of time series. For example, in environmental health applications TSS could be used to identify short-term patterns in exposure time series (shapelets) associated with adverse health outcomes. Identification of candidate shapelets in TSS is computationally intensive. The original TSS algorithm used exhaustive search. Subsequent algorithms introduced efficiencies by trimming/aggregating the set of candidates or training candidates from initialized values, but these approaches have limitations. In this paper, we introduce Wavelet-TSS (W-TSS) a novel intelligent method for identifying candidate shapelets in TSS using wavelet transformation discovery. We tested W-TSS on two datasets: (1) a synthetic example used in previous TSS studies and (2) a panel study relating exposures from residential air pollution sensors to symptoms in participants with asthma. Compared to previous TSS algorithms, W-TSS was more computationally efficient, more accurate, and was able to discover more discriminative shapelets. W-TSS does not require pre-specification of shapelet length.},
DOI = {10.3390/s21175801}
}
@INPROCEEDINGS{Yue2021-aa,
title = "{VAMBC: A Variational Approach for Mobility Behavior Clustering}",
booktitle = "{Machine Learning and Knowledge Discovery in Databases. Applied
Data Science Track}",
author = "Yue, Mingxuan and Chiang, Yao-Yi and Shahabi, Cyrus",
publisher = "Springer International Publishing",
pages = "453--469",
year = 2021,
url = "http://dx.doi.org/10.1007/978-3-030-86514-6_28",
doi = "10.1007/978-3-030-86514-6_28"
}
@ARTICLE{Uhl2021-dj,
title = "{Combining Remote-Sensing-Derived Data and Historical Maps for
Long-Term Back-Casting of Urban Extents}",
author = "Uhl, Johannes H and Leyk, Stefan and Li, Zekun and Duan, Weiwei
and Shbita, Basel and Chiang, Yao-Yi and Knoblock, Craig A",
journal = "Remote Sensing",
publisher = "Multidisciplinary Digital Publishing Institute",
volume = 13,
number = 18,
pages = "3672",
month = sep,
year = 2021,
url = "https://www.mdpi.com/2072-4292/13/18/3672",
file = "yaoyichi.github.io/papers-all//Uhl-et-al.-2021-Combining-Remote-Sensing-Derived-Data-and-Historical-Maps-for-Long-Term-Back-Casting-of-Urban-Extents.pdf",
language = "en",
doi = "10.3390/rs13183672"
}
@INPROCEEDINGS{Lin2020-kk,
title = "{Building Autocorrelation-Aware Representations for Fine-Scale
Spatiotemporal Prediction}",
booktitle = "{Proceedings of IEEE International Conference on Data Mining
(ICDM)}",
author = "Lin, Y and Chiang, Y-Y and Franklin, M and Eckel, P S and
Ambite, J L",
year = 2020,
url-file = "papers/Lin-et-al.-2020-Building-Autocorrelation-Aware-Representations-for-Fine-Scale-Spatiotemporal-Prediction.pdf"
}
@MISC{Chiang2016-hc,
title = "{Exploiting Context in Cartographic Evolutionary Documents to
Extract and Build Linked Spatial-Temporal Datasets}",
author = "Chiang, Y Y",
year = 2016,
howpublished = "2016 Conference on Complex Systems, Complex Systems Society",
location = "Amsterdam, Netherlands"
}
@INPROCEEDINGS{Leyk2017-zc,
title = "{Implementing the Concept of Geographic Context for Efficient
Recognition from Large-Scale Topographic Map Series}",
booktitle = "{Proceedings of the 28th International Cartographic Conference}",
author = "Leyk, Stefan and Chiang, Yao-Yi",
year = 2017
}
@INPROCEEDINGS{Nanetti2017-tf,
title = "{Visual Knowledge Aggregation: From Static to Dynamic Information
Systems in Library Contexts}",
booktitle = "{Proceedings of the ICA Pre-Conference Workshop on Mapping Tools
for Non-Mapping Experts: Incorporating Geospatial Visualization
Tools in Libraries}",
author = "Nanetti, A and Cattaneo, A and Cheong, S A and Chiang, Y Y and
Lin, C Y",
year = 2017
}
@INPROCEEDINGS{Chiang2017-qn,
title = "{Automatic Learning of User Design Rationales from Examples}",
booktitle = "{Proceedings of the Symposium on Solid and Physical Modeling
(SPM)}",
author = "Chiang, Y Y and Jain, A and Bandyopadhyay, B and Knoblock, A C",
year = 2017,
url-file = "papers/Chiang-et-al.-2017-Automatic-Learning-of-User-Design-Rationales-from-Examples.pdf"
}
@MISC{Holmes-Wong2017-ti,
title = "{Unlocking Maps for Discovery and Other Purpose}",
author = "Holmes-Wong, D and Chiang, Y Y",
year = 2017,
howpublished = "Digital Library Federation (DLF) Forum",
location = "Pittsburg, PA, USA"
}
@INPROCEEDINGS{Duan2017-de,
title = "{Automatic alignment of geographic features in contemporary
vector data and historical maps}",
booktitle = "{Proceedings of the 1st Workshop on Artificial Intelligence and
Deep Learning for Geographic Knowledge Discovery}",
author = "Duan, Weiwei and Chiang, Yao-Yi and Knoblock, Craig A and Jain,
Vinil and Feldman, Dan and Uhl, Johannes H and Leyk, Stefan",
publisher = "Association for Computing Machinery",
pages = "45--54",
series = "GeoAI '17",
month = nov,
year = 2017,
url = "https://doi.org/10.1145/3149808.3149816",
url-file = "papers/Duan-et-al.-2017-Automatic-alignment-of-geographic-features-in-contemporary-vector-data-and-historical-maps.pdf",
address = "New York, NY, USA",
location = "Los Angeles, California",
isbn = "9781450354981",
doi = "10.1145/3149808.3149816"
}
@MISC{Uhl2017-im,
title = "{Machine-learning based Approaches for Extracting Settlement
Features from Historical Maps}",
author = "Uhl, Johannes H and Leyk, Stefan and Chiang, Yao-Yi and Duan,
Weiwei and Knoblock, Craig A",
year = 2017,
howpublished = "The International Land Use Symposium 2017 (Spatial data
modelling and visualisation to enlighten sustainable policy
making)",
location = "Dresden, Germany"
}
@MISC{Chiang2018-ls,
title = "{Next Generation Framework for Imagery Recognition and
Analysis}",
author = "Chiang, Y Y and Feldman, D",
year = 2018,
howpublished = "The 1st workshop of the NSF project: SI2-S2I2
Conceptualization: Geospatial Software Institute (GSI)",
url-file = "papers/Chiang-and-Feldman-2018-Next-Generation-Framework-for-Imagery-Recognition-and-Analysis.pdf"
}
@INPROCEEDINGS{Yu2018-tj,
title = "{MAPINS: An Intra-City PM2.5 Modeling Web Application Using A
Scalable Data Management and Analysis System Integrating Public
Multi-Source Data}",
booktitle = "{Proceedings of the AutoCarto}",
author = "Yu, X and Cheng, Y and Lin, Y and Chiang, Y Y and Stripelis, D
and Ambite, J L",
pages = "135 -- 145",
year = 2018,
url-file = "papers/Yu-et-al.-2018-MAPINS-An-Intra-City-PM2.5-Modeling-Web-Application-U...-a-Management-and-Analysis-System-Integrating-Public-Multi-Source-Data.pdf"
}
@INPROCEEDINGS{Duan2018-cx,
title = "{Automatic generation of precisely delineated geographic features
from georeferenced historical maps using deep learning}",
booktitle = "{Proceedings of the AutoCarto}",
author = "Duan, Weiwei and Chiang, Y and Knoblock, Crang A and Leyk,
Stefan and Uhl, J",
pages = "59--63",
year = 2018,
url-file = "papers/Duan-et-al.-2018-Automatic-generation-of-precisely-delineated-geographic-features-from-georeferenced-historical-maps-using-deep-learning.pdf"
}
@INPROCEEDINGS{Uhl2018-cf,
title = "{Exploring the Potential of Deep Learning for Settlement Symbol
Extraction from Historical Map Documents}",
booktitle = "{Proceedings of the UCGIS/AutoCarto}",
author = "Uhl, Johannes H and Leyk, Stefan and Chiang, Yao-Yi and Duan,
Weiwei and Knoblock, Craig A",
pages = "123 -- 124",
year = 2018,
url-file = "papers/Uhl-et-al.-2018-Exploring-the-Potential-of-Deep-Learning-for-Settlement-Symbol-Extraction-from-Historical-Map-Documents.pdf"
}
@INPROCEEDINGS{Gil2018-hg,
title = "{MINT: Model Integration Through Knowledge-Powered Data and
Process Composition}",
booktitle = "{Proceedings of the 9th International Congress on Environmental
Modelling and Software}",
author = "Gil, Yolanda and Cobourn, Kelly and Deelman, Ewa and Duffy,
Chris and da Silva, Rafael Ferreira and Kemanian, Armen and
Knoblock, Craig and Kumar, Vipin and Peckham, Scott and
Carvalho, Lucas and Chiang, Yao-Yi and Garijo, Daniel and
Khider, Deborah and Khandelwal, Ankush and Pahm, Minh and
Pujara, Jay and Ratnakar, Varun and Stoica, Maria and Vu, Binh",
year = 2018,
url-file = "papers/Gil-et-al.-2018-MINT-Model-Integration-Through-Knowledge-Powered-Data-and-Process-Composition.pdf"
}
@INPROCEEDINGS{Lin2018-ck,
title = "{Building Linked Data from Historical Maps}",
booktitle = "{Proceedings of the SemSci 2018: Enabling Open Semantic Science}",
author = "Lin, Chun and Su, Hang and Knoblock, Craig A and Chiang, Yao-Yi
and Duan, Weiwei and Leyk, Stefan and Uhl, Johannes H",
pages = "59--67",
year = 2018,
url = "ftp://ceur-ws.org/pub/publications/CEUR-WS/Vol-2184.zip",
url-file = "papers/Lin-et-al.-2018-Building-Linked-Data-from-Historical-Maps.pdf"
}
@INPROCEEDINGS{Lin2018-vk,
title = "{An Uncertainty Aware Method for Geographic Data Conflation}",
booktitle = "{Proceedings of the 7th ACM SIGSPATIAL International Workshop on
Analytics for Big Geospatial Data}",
author = "Lin, Haowen and Chiang, Yao-Yi",
publisher = "Association for Computing Machinery",
pages = "20--27",
series = "BigSpatial 2018",
month = nov,
year = 2018,
url = "https://doi.org/10.1145/3282834.3282842",
url-file = "papers/Lin-and-Chiang-2018-An-Uncertainty-Aware-Method-for-Geographic-Data-Conflation.pdf",
address = "New York, NY, USA",
location = "Seattle, WA, USA",
isbn = "9781450360418",
doi = "10.1145/3282834.3282842"
}
@INPROCEEDINGS{Nguyen2018-am,
title = "{Los angeles metro bus data analysis using GPS trajectory and
schedule data (demo paper)}",
booktitle = "{Proceedings of the 26th ACM SIGSPATIAL International Conference
on Advances in Geographic Information Systems}",
author = "Nguyen, Kien and Yang, Jingyun and Lin, Yijun and Lin, Jianfa
and Chiang, Yao-Yi and Shahabi, Cyrus",
publisher = "Association for Computing Machinery",
pages = "560--563",
series = "SIGSPATIAL '18",
month = nov,
year = 2018,
url = "https://doi.org/10.1145/3274895.3274911",
url-file = "papers/Nguyen-et-al.-2018-Los-angeles-metro-bus-data-analysis-using-GPS-trajectory-and-schedule-data-(demo-paper).pdf",
address = "New York, NY, USA",
location = "Seattle, Washington",
isbn = "9781450358897",
doi = "10.1145/3274895.3274911"
}
@ARTICLE{Cheng2019-mi,
title = "{Automatic intersection extraction and building arrangement with
StarCraft II maps}",
author = "Cheng, Yuanbin and Chiang, Yao-Yi",
journal = "SIGSPATIAL Special",
publisher = "Association for Computing Machinery",
volume = 10,
number = 3,
pages = "4--5",
month = jan,
year = 2019,
url = "https://doi.org/10.1145/3307599.3307602",
url-file = "papers/Cheng-and-Chiang-2019-Automatic-intersection-extraction-and-building-arrangement-with-StarCraft-II-maps.pdf",
address = "New York, NY, USA",
doi = "10.1145/3307599.3307602"
}
@INPROCEEDINGS{Garijo2019-yw,
title = "{An intelligent interface for integrating climate, hydrology,
agriculture, and socioeconomic models}",
booktitle = "{Proceedings of the 24th International Conference on Intelligent
User Interfaces: Companion}",
author = "Garijo, Daniel and Khider, Deborah and Ratnakar, Varun and Gil,
Yolanda and Deelman, Ewa and da Silva, Rafael Ferreira and
Knoblock, Craig and Chiang, Yao-Yi and Pham, Minh and Pujara,
Jay and Vu, Binh and Feldman, Dan and Mayani, Rajiv and Cobourn,
Kelly and Duffy, Chris and Kemanian, Armen and Shu, Lele and
Kumar, Vipin and Khandelwal, Ankush and Tayal, Kshitij and
Peckham, Scott and Stoica, Maria and Dabrowski, Anna and
Hardesty-Lewis, Daniel and Pierce, Suzanne",
publisher = "Association for Computing Machinery",
pages = "111--112",
series = "IUI '19",
month = mar,
year = 2019,
url = "https://doi.org/10.1145/3308557.3308711",
url-file = "papers/Garijo-et-al.-2019-An-intelligent-interface-for-integrating-climate,-hydrology,-agriculture,-and-socioeconomic-models.pdf",
address = "New York, NY, USA",
location = "Marina del Ray, California",
isbn = "9781450366731",
doi = "10.1145/3308557.3308711"
}
@INPROCEEDINGS{Zhang2019-cl,
title = "{A VLOS Compliance Solution to Ground/Aerial Parcel Delivery
Problem}",
booktitle = "{Proceedings of the 2019 20th IEEE International Conference on
Mobile Data Management (MDM)}",
author = "Zhang, J and Shen, T and Wang, W and Jiang, X and Ku, W and Sun,
M and Chiang, Y Y",
pages = "201--209",
month = jun,
year = 2019,
url = "http://dx.doi.org/10.1109/MDM.2019.00-56",
url-file = "papers/Zhang-et-al.-2019-A-VLOS-Compliance-Solution-to-Ground-Aerial-Parcel-Delivery-Problem.pdf",
issn = "2375-0324",
doi = "10.1109/MDM.2019.00-56"
}
@INPROCEEDINGS{Shbita2019-lv,
title = "{Creating a FAIR Data Catalog to Support Scientific Modeling}",
booktitle = "{Proceedings of the Workshop on Advanced Knowledge Technologies
for Science in a FAIR World (AKTS) 2019}",
author = "Shbita, Basel and Vu, Binh and Feldman, Dan and Pham, Minh and
Rajendran, A and Knoblock, C A and Pujara, J and Chiang, Y-Y",
month = sep,
year = 2019,
url = "https://www.researchgate.net/publication/339670920_Creating_a_FAIR_Data_Catalog_to_Support_Scientific_Modeling",
url-file = "papers/Shbita-et-al.-2019-Creating-a-FAIR-Data-Catalog-to-Support-Scientific-Modeling.pdf"
}
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title = "{Personalized Recommendation Method of POI Based on Deep Neural
Network}",
booktitle = "{Proceedings of the 2019 6th International Conference on
Behavioral, Economic and Socio-Cultural Computing (BESC)}",
author = "Gao, Y and Duan, Z and Shi, W and Feng, J and Chiang, Y-Y",
pages = "1--6",
month = oct,
year = 2019,
url = "http://dx.doi.org/10.1109/BESC48373.2019.8963449",
url-file = "papers/Gao-et-al.-2019-Personalized-Recommendation-Method-of-POI-Based-on-Deep-Neural-Network.pdf",
doi = "10.1109/BESC48373.2019.8963449"
}
@ARTICLE{Chiang2014-gr,
title = "{A Survey of Digital Map Processing Techniques}",
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volume = 47,
number = 1,
pages = "1--44",
month = may,
year = 2014,
url = "https://doi.org/10.1145/2557423",
url-file = "papers/Chiang-et-al.-2014-A-Survey-of-Digital-Map-Processing-Techniques.pdf",
address = "New York, NY, USA",
issn = "0360-0300",
doi = "10.1145/2557423"
}
@ARTICLE{Wu2016-io,
title = "{Q2P: Discovering Query Templates via Autocompletion}",
author = "Wu, Wensheng and Meng, Weiyi and Su, Weifeng and Zhou, Guangyou
and Chiang, Yao-Yi",
journal = "ACM Trans. Web",
publisher = "Association for Computing Machinery",
volume = 10,
number = 2,
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month = apr,
year = 2016,
url = "https://doi.org/10.1145/2873061",
url-file = "papers/Wu-et-al.-2016-Q2P-Discovering-Query-Templates-via-Autocompletion.pdf",
address = "New York, NY, USA",
issn = "1559-1131",
doi = "10.1145/2873061"
}
@ARTICLE{Duan2018-rv,
title = "{SRC: a fully automatic geographic feature recognition system}",
author = "Duan, Weiwei and Chiang, Yao-Yi",
journal = "SIGSPATIAL Special",
publisher = "Association for Computing Machinery",
volume = 9,
number = 3,
pages = "6--7",
month = jan,
year = 2018,
url = "https://doi.org/10.1145/3178392.3178396",
url-file = "papers/Duan-and-Chiang-2018-SRC-a-fully-automatic-geographic-feature-recognition-system.pdf",
address = "New York, NY, USA",
doi = "10.1145/3178392.3178396"
}
@ARTICLE{Wu2018-nr,
title = "{A Matching Algorithm Based on Voronoi Diagram for Multi-Scale
Polygonal Residential Areas}",
author = "Wu, J and Wan, Y and Chiang, Y Y and Fu, Z and Deng, M",
journal = "IEEE Access",
volume = 6,
pages = "4904--4915",
year = 2018,
url = "http://dx.doi.org/10.1109/ACCESS.2018.2793302",
url-file = "papers/Wu-et-al.-2018-A-Matching-Algorithm-Based-on-Voronoi-Diagram-for-Multi-Scale-Polygonal-Residential-Areas.pdf",
issn = "2169-3536",
doi = "10.1109/ACCESS.2018.2793302"
}
@ARTICLE{VoPham2018-zv,
title = "{Emerging trends in geospatial artificial intelligence (geoAI):
potential applications for environmental epidemiology}",
author = "VoPham, Trang and Hart, Jaime E and Laden, Francine and Chiang,
Yao-Yi",
journal = "Environmental health: a global access science source",
volume = 17,
number = 1,
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month = apr,
year = 2018,
url = "http://dx.doi.org/10.1186/s12940-018-0386-x",
url-file = "papers/VoPham-et-al.-2018-Emerging-trends-in-geospatial-artificial-intelligence-(geoAI)-potential-applications-for-environmental-epidemiology.pdf",
language = "en",
issn = "1476-069X",
pmid = "29665858",
doi = "10.1186/s12940-018-0386-x",
pmc = "PMC5905121"
}
@ARTICLE{Li2019-gr,
title = "{Applying Multivariate Segmentation Methods to Human Activity
Recognition From Wearable Sensors' Data}",
author = "Li, Kenan and Habre, Rima and Deng, Huiyu and Urman, Robert and
Morrison, John and Gilliland, Frank D and Ambite, Jos{\'e} Luis
and Stripelis, Dimitris and Chiang, Yao-Yi and Lin, Yijun and
Bui, Alex At and King, Christine and Hosseini, Anahita and Van
Vliet, Eleanne and Sarrafzadeh, Majid and Eckel, Sandrah P",
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month = feb,
year = 2019,
url = "http://dx.doi.org/10.2196/11201",
url-file = "papers/Li-et-al.-2019-Applying-Multivariate-Segmentation-Methods-to-Human-Activity-Recognition-From-Wearable-Sensors'-Data.pdf",
language = "en",
issn = "2291-5222",
pmid = "30730297",
doi = "10.2196/11201",
pmc = "PMC6386646"
}
@ARTICLE{Wu2019-qe,
title = "{A New Gabor Filter-Based Method for Automatic Recognition of
Hatched Residential Areas}",
author = "Wu, J and Wei, P and Yuan, X and Shu, Z and Chiang, Y Y and Fu, Z
and Deng, M",
journal = "IEEE Access",
volume = 7,
pages = "40649--40662",
year = 2019,
url = "http://dx.doi.org/10.1109/ACCESS.2019.2907114",
url-file = "papers/Wu-et-al.-2019-A-New-Gabor-Filter-Based-Method-for-Automatic-Recognition-of-Hatched-Residential-Areas.pdf",
issn = "2169-3536",
doi = "10.1109/ACCESS.2019.2907114"
}
@ARTICLE{Zhang2019-rj,
title = "{Extracting geographic features from the Internet: A geographic
information mining framework}",
author = "Zhang, Ying and Ma, Qunfei and Chiang, Yao-Yi and Knoblock, Craig
and Zhang, Xin and Yang, Puhai and Gao, Minghe and Hu, Xiang",
journal = "Knowledge-Based Systems",
volume = 174,
pages = "57--72",
month = jun,
year = 2019,
url = "http://www.sciencedirect.com/science/article/pii/S0950705119300929",
url-file = "papers/Zhang-et-al.-2019-Extracting-geographic-features-from-the-Internet-A-geographic-information-mining-framework.pdf",
issn = "0950-7051",
doi = "10.1016/j.knosys.2019.02.031"
}
@ARTICLE{Duan2020-wl,
title = "{Automatic alignment of contemporary vector data and
georeferenced historical maps using reinforcement learning}",
author = "Duan, Weiwei and Chiang, Yao-Yi and Leyk, Stefan and Uhl,
Johannes H and Knoblock, Craig A",
journal = "International journal of geographical information science: IJGIS",
publisher = "Taylor \& Francis",
volume = 34,
number = 4,
pages = "824--849",
month = apr,
year = 2020,
url = "https://doi.org/10.1080/13658816.2019.1698742",
url-file = "papers/Duan-et-al.-2020-Automatic-alignment-of-contemporary-vector-data-and-georeferenced-historical-maps-using-reinforcement-learning.pdf",
issn = "1365-8816",
doi = "10.1080/13658816.2019.1698742"
}
@ARTICLE{Zhang2020-rb,
title = "{Efficient Deployment of Electric Vehicle Charging Infrastructure:
Simultaneous Optimization of Charging Station Placement and
Charging Pile Assignment}",
author = "Zhang, Y and Wang, Y and Li, F and Wu, B and Chiang, Y Y and
Zhang, X",
journal = "IEEE Transactions on Intelligent Transportation Systems",
pages = "1--6",
year = 2020,
url = "http://dx.doi.org/10.1109/TITS.2020.2990694",
url-file = "papers/Zhang-et-al.-2020-Efficient-Deployment-of-Electric-Vehicle-Charging-In...-timization-of-Charging-Station-Placement-and-Charging-Pile-Assignment.pdf",
issn = "1558-0016",
doi = "10.1109/TITS.2020.2990694"
}
@INCOLLECTION{Chiang2010-rk,
title = "{Extracting Road Vector Data from Raster Maps}",
booktitle = "{Graphics Recognition. Achievements, Challenges, and Evolution.
GREC 2009. Lecture Notes in Computer Science}",
author = "Chiang, Yao-Yi and Knoblock, Craig A",
editor = "Ogier, J M and ., Liu W and J., Llad{\'o}s",
publisher = "Springer Berlin Heidelberg",
volume = 6020,
pages = "93--105",
year = 2010,
url = "http://dx.doi.org/10.1007/978-3-642-13728-0_9",
url-file = "papers/Chiang-and-Knoblock-2010-Extracting-Road-Vector-Data-from-Raster-Maps.pdf",
doi = "10.1007/978-3-642-13728-0\_9"
}
@INCOLLECTION{Park2016-ht,
title = "{Hot Spots of Tweets Related to Food, Entertainment, Work, and
Study in Gangnam Area of Seoul, Korea}",
booktitle = "{Esri Map Book}",
author = "Park, W and Chiang, Y-Y and Lee, S J and Yu, K",
publisher = "Esri",
volume = "31: GIS -- Enabling a Smarter World. Redlands",
year = 2016
}
@BOOK{Chiang2020-vm,
title = "{Using Historical Maps in Scientific Studies: Applications,
Challenges, and Best Practices}",
author = "Chiang, Yao-Yi and Duan, Weiwei and Leyk, Stefan and Uhl,
Johannes H and Knoblock, Craig A",
publisher = "Springer International Publishing",
series = "SpringerBriefs in Geography",
year = 2020,
url = "https://link.springer.com/book/10.1007/978-3-319-66908-3",
url-file = "papers/Chiang-et-al.-2020-Using-Historical-Maps-in-Scientific-Studies-Applications,-Challenges,-and-Best-Practices.pdf",
isbn = "9783319669076",
doi = "10.1007/978-3-319-66908-3"
}
@INCOLLECTION{Chiang2020-zz,
title = "{Design, Development, Testing, and Deployment of GIS Applications}",
booktitle = "{The Geographic Information Science \& Technology Body of
Knowledge (4th Quarter 2020 Edition)}",
author = "Chiang, Yao-Yi and Lin, Yijun",
editor = "Wilson, John P",
publisher = "The University Consortium for Geographic Information Science
(UCGIS)",
year = 2020,
url = "http://dx.doi.org/10.22224/gistbok/2020.4.2",
url-file = "papers/Chiang-and-Lin-2020-Design,-Development,-Testing,-and-Deployment-of-GIS-Applications.pdf",
doi = "10.22224/gistbok/2020.4.2"
}
@INPROCEEDINGS{Chiang2019-yx,
title = "{Building Explainable Predictive Analytics for Location-Dependent
Time-Series Data}",
booktitle = "{Proceedings of the 2019 IEEE First International Conference on
Cognitive Machine Intelligence (CogMI)}",
author = "Chiang, Y Y and Lin, Y and Franklin, M and Eckel, S P and
Ambite, J L and Ku, W",
pages = "202--209",
month = dec,
year = 2019,
url = "http://dx.doi.org/10.1109/CogMI48466.2019.00037",
url-file = "papers/Chiang-et-al.-2019-Building-Explainable-Predictive-Analytics-for-Location-Dependent-Time-Series-Data.pdf",
doi = "10.1109/CogMI48466.2019.00037"
}
@INPROCEEDINGS{Lin2017-go,
title = "{Mining Public Datasets for Modeling Intra-City PM2.5
Concentrations at a Fine Spatial Resolution}",
booktitle = "{Proceedings of the 25th ACM SIGSPATIAL International Conference
on Advances in Geographic Information Systems}",
author = "Lin, Yijun and Chiang, Yao-Yi and Pan, Fan and Stripelis,
Dimitrios and Ambite, Jose Luis and Eckel, Sandrah P and Habre,
Rima",
publisher = "ACM",
volume = 8,
pages = "1--10",
month = nov,
year = 2017,
url = "https://dl.acm.org/doi/10.1145/3139958.3140013",
url-file = "papers/Lin-et-al.-2017-Mining-Public-Datasets-for-Modeling-Intra-City-PM2.5-Concentrations-at-a-Fine-Spatial-Resolution.pdf",
address = "New York, NY, USA",
language = "en",
conference = "SIGSPATIAL'17: 25th ACM SIGSPATIAL International Conference on
Advances in Geographic Information Systems",
location = "Redondo Beach CA USA",
isbn = "9781450354905",
pmid = "29527599",
doi = "10.1145/3139958.3140013",
pmc = "PMC5841919"
}
@INPROCEEDINGS{Anastasiou2019-gk,
title = "{ADMSv2: A Modern Architecture for Transportation Data Management
and Analysis}",
booktitle = "{Proceedings of the 2nd ACM SIGSPATIAL workshop ARIC'19}",
author = "Anastasiou, Chrysovalantis and Lin, Jianfa and He, Chaoyang and
Chiang, Yao-Yi and Shahabi, Cyrus",
year = 2019,
url-file = "papers/Anastasiou-et-al.-2019-ADMSv2-A-Modern-Architecture-for-Transportation-Data-Management-and-Analysis.pdf;papers/Anastasiou-et-al.-2019-ADMSv2-A-Modern-Architecture-for-Transportation-Data-Management-and-Analysis.pdf",
address = "New York"
}
@INPROCEEDINGS{Yue2019-hn,
title = "{DETECT: Deep Trajectory Clustering for Mobility-Behavior
Analysis}",
booktitle = "{Proceedings of the 2019 IEEE International Conference on Big
Data (Big Data)}",
author = "Yue, M and Li, Y and Yang, H and Ahuja, R and Chiang, Y and
Shahabi, C",
pages = "988--997",
month = dec,
year = 2019,
url = "http://dx.doi.org/10.1109/BigData47090.2019.9006561",
url-file = "papers/Yue-et-al.-2019-DETECT-Deep-Trajectory-Clustering-for-Mobility-Behavior-Analysis.pdf",
doi = "10.1109/BigData47090.2019.9006561"
}
@ARTICLE{Lin2018-wz,
title = "{SRC: automatic extraction of phrase-level map labels from
historical maps}",
author = "Lin, Haowen and Chiang, Yao-Yi",
journal = "SIGSPATIAL Special",
publisher = "Association for Computing Machinery",
volume = 9,
number = 3,
pages = "14--15",
month = jan,
year = 2018,
url = "https://doi.org/10.1145/3178392.3178400",
url-file = "papers/Lin-and-Chiang-2018-SRC-automatic-extraction-of-phrase-level-map-labels-from-historical-maps.pdf",
address = "New York, NY, USA",
doi = "10.1145/3178392.3178400"
}
@INPROCEEDINGS{Lin2018-xw,
title = "{Exploiting spatiotemporal patterns for accurate air quality
forecasting using deep learning}",
booktitle = "{Proceedings of the 26th ACM SIGSPATIAL International Conference
on Advances in Geographic Information Systems}",
author = "Lin, Yijun and Mago, Nikhit and Gao, Yu and Li, Yaguang and
Chiang, Yao-Yi and Shahabi, Cyrus and Ambite, Jos{\'e} Luis",
publisher = "Association for Computing Machinery",
pages = "359--368",
series = "SIGSPATIAL '18",
month = nov,
year = 2018,
url = "https://doi.org/10.1145/3274895.3274907",
url-file = "papers/Lin-et-al.-2018-Exploiting-spatiotemporal-patterns-for-accurate-air-quality-forecasting-using-deep-learning.pdf",
address = "New York, NY, USA",
location = "Seattle, Washington",
isbn = "9781450358897",
doi = "10.1145/3274895.3274907"
}
@INPROCEEDINGS{Tavakkol2019-xs,
title = "{Kartta Labs: Unrendering Historical Maps}",
booktitle = "{Proceedings of the 3rd ACM SIGSPATIAL International Workshop on
AI for Geographic Knowledge Discovery}",
author = "Tavakkol, Sasan and Chiang, Yao-Yi and Waters, Tim and Han, Feng
and Prasad, Kisalaya and Kiveris, Raimondas",
publisher = "Association for Computing Machinery",
pages = "48--51",
series = "GeoAI 2019",
month = nov,
year = 2019,
url = "https://doi.org/10.1145/3356471.3365236",
url-file = "papers/Tavakkol-et-al.-2019-Kartta-Labs-Unrendering-Historical-Maps.pdf",
address = "New York, NY, USA",
location = "Chicago, IL, USA",
isbn = "9781450369572",
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