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Chun, Soon
City University of New York
Staten Island, New York
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Soon Ae Chun is a City University of New York (CUNY) College of Staten Island (CSI) professor and director of its Information Systems and Informatics (ISI) program. She also teaches at the CUNY Graduate Center (GC) in both the computer science PhD program and the Master’s program in data science. She is the director of the National Science Foundation (NSF)-sponsored Information Security Research and Education Lab (iSecure Lab). In 2018, she was awarded a Fulbright Senior Scholarship. She received the CSI President’s Dolphin Award for Outstanding Scholarly Achievement in 2014.

Dr. Chun applies data management, data analytics, machine learning, and semantic web and knowledge-based approaches to security, privacy, digital government, smart cities, and digital health. She served as president of the Digital Government Society from 2016 to 2017, and is a founding editor-in-chief of Digital Government: Research and Practice (DGOV).

Her research has been funded by NSF, the National Oceanic and Atmospheric Administration (NOAA), New Jersey state government agencies, the National Research Foundation of Korea, and the Professional Staff Congress (PSC-CUNY). She is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM).

She has been a CR reviewer since 2013.

Date Reviewed  
- 10 of 29 reviews

  Understanding movement in context with heterogeneous data
Derin O., Mitra A., Stroila M., Custers B., Meulemans W., Roeloffzen M., Verbeek K.  MOVE 2019 (Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data, Chicago, IL,  Nov 5, 2019) 1-4, 2019. Type: Proceedings

Mobility studies on humans, vehicles, and animals involve trajectory data, which allows for location tracking over time per entity. Trajectory data can help with analyzing and understanding the location information of an entity or a crowd, the flo...

Sep 22 2021  
  Coding-data portability in systematic literature reviews: a W3C’s open annotation approach
Díaz O., Medina H., Anfurrutia F.  EASE 2019 (Proceedings of the Evaluation and Assessment on Software Engineering, Copenhagen, Denmark,  Apr 15-17, 2019) 178-187, 2019. Type: Proceedings

Systematic literature reviews (SLRs) involve several steps: the planning step, which identifies the scope of literature according to the research goals, and develops a coding protocol; the analysis step, which performs searching for relevant liter...

Apr 9 2021  
  Linked open knowledge organization systems: definition of a method for reducing the traversing
Chicaiza J., Tapia-Leon M., Piedra N., Lopez-Vargas J., Tovar-Caro E.  APPIS 2019 (Proceedings of the 2nd International Conference on Applications of Intelligent Systems, Las Palmas de Gran Canaria, Spain,  Jan 7-9, 2019) 1-6, 2019. Type: Proceedings

Knowledge organization systems (KOS) allow for establishing and accessing a common vocabulary and concepts in a domain. Linked data refers to a semantic web knowledge organization method that links concepts by relationships on the web to facilitat...

Jan 5 2021  
   A survey on deep learning: algorithms, techniques, and applications
Pouyanfar S., Sadiq S., Yan Y., Tian H., Tao Y., Reyes M., Shyu M., Chen S., Iyengar S.  ACM Computing Surveys 51(5): 1-36, 2018. Type: Article

Deep learning (DL) algorithms, characterized by mapping from input to output (labels or classes) with multiple hidden layers in between, have revived the excitement of artificial intelligence (AI) to get closer to its initial vision of building in...

Oct 16 2020  
  Deep item-based collaborative filtering for top-N recommendation
Xue F., He X., Wang X., Xu J., Liu K., Hong R.  ACM Transactions on Information Systems 37(3): 1-25, 2019. Type: Article

Recommender systems are an essential component in digital platforms, nudging consumers toward more efficient decision making by predicting and presenting products and services in a personalized ranking order that is of top interest. By filtering o...

Nov 19 2019  
   Searching for global employability: can students capitalize on enabling learning environments?
Isomöttönen V., Daniels M., Cajander Å., Pears A., Mcdermott R.  ACM Transactions on Computing Education (TOCE) 19(2): 1-29, 2019. Type: Article, Reviews: (2 of 2)

Today’s higher education systems need to produce graduates with global employability that exhibits creativity and innovation, that is, the ability to solve open-ended problems in different cultural settings, but also domain-specific skill se...

May 3 2019  
  How to live in a post-Meltdown and -Spectre world
Bennett R., Callahan C., Jones S., Levine M., Miller M., Ozment A.  Communications of the ACM 61(12): 40-44, 2018. Type: Article

Handling zero-day vulnerabilities means making decisions under uncertainty and taking preventive actions for potential exploits. As Meltdown and Spectre attacks may exploit the vulnerabilities that stem from the fundamental design features of most...

Mar 5 2019  
  Large-scale ontology matching: state-of-the-art analysis
Ochieng P., Kyanda S.  ACM Computing Surveys 51(4): 1-35, 2018. Type: Article

The ontology matching or alignment task identifies inconsistencies among concepts, relationships, and instances in two different ontologies and then resolves correspondence relationships. The authors present a survey of ontology matching technique...

Jan 25 2019  
  Discovering and understanding Android sensor usage behaviors with data flow analysis
Liu X., Liu J., Wang W., He Y., Zhang X.  World Wide Web 21(1): 105-126, 2018. Type: Article

From 2008 to 2018, the use of mobile apps has grown exponentially, reaching more than 3.8 million apps in Google’s Play Store and two million apps in Apple’s App Store, followed by numerous other apps available from Amazon, Microsoft, ...

Jul 6 2018  
  Detecting cooperative and organized spammer groups in micro-blogging community
Dang Q., Zhou Y., Gao F., Sun Q.  Data Mining and Knowledge Discovery 31(3): 573-605, 2017. Type: Article

Public relations (PR) companies hire and pay cooperative and organized spammer groups to post specific content on online microblogging sites, such as Twitter, to influence public opinion or trending topics (topic hijacking). Detecting such spammer...

Jan 4 2018  
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