Guang is a fifth year Ph.D. student at the Language Technologies Institute in the School of Computer Science at Carnegie Mellon.
His research interests include anti-phishing and mining interesting patterns from big data via machine learning, data mining, computer vision and other techniques.
Publications
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A Supervised Approach to Predict Company Acquisition with Factual and Topic Features Using Profiles and News Articles on TechCrunch
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Guang Xiang, Zeyu Zheng, Miaomiao Wen, Jason Hong, Carolyn Rose, and Chao Liu |
International AAAI Conference on Weblogs and Social Media (ICWSM) |
Work in Progress |
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Detecting Offensive Tweets via Topical Feature Discovery over a Large Scale Twitter Corpus
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Guang Xiang, Bin Fan, Ling Wang, Jason Hong, and Carolyn P. Rose |
Conference on Information and Knowledge Management (CIKM) |
Work in Progress |
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Smartening the Crowds: Computational Techniques for Improving Human Verification to Fight Phishing Scams
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Gang Liu, Guang Xiang, Bryan Pendleton, Jason Hong, and Wenyin Liu |
Symposium on Usable Privacy and Security (SOUPS) |
Full Paper |
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CANTINA+: A Feature-rich Machine Learning Framework for Detecting Phishing Web Sites
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Guang Xiang, Jason Hong, Carolyn Rose, and Lorrie Cranor |
ACM Transactions on Information Systems and Security (ACM TISSEC) |
Journal Article |
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A Hierarchical Adaptive Probabilistic Approach for Zero Hour Phish Detection
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Guang Xiang, Carolyn Rose, Jason Hong, and Bryan Pendleton |
European Symposium on Research in Computer Security (ESORICS) |
Full Paper |
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Modeling People’s Place Naming Preferences in Location Sharing
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Jialiu Lin, Guang Xiang, Jason Hong, and Norman Sadeh |
International Conference on Ubiquitous Computing (Ubicomp) |
Full Paper |
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A Hybrid Phish Detection Approach by Identity Discovery and Keywords Retrieval
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Guang Xiang and Jason Hong |
International Conference on World Wide Web (WWW) |
Full Paper |
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Modeling Content from Human-Verified Blacklists for Accurate Zero-Hour Phish Detection
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Guang Xiang, Bryan A. Pendleton, and Jason Hong |
CMU SCS Technical Report: CMU-LTI-09-005 |
Technical Report |
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Clever Clustering vs. Simple Speed-up for Summarizing Rushes
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Alexander G. Hauptmann, Michael G. Christel, Wei-Hao Lin, Bryan Maher, Jun Yang, Robert V. Baron, and Guang Xiang |
International workshop on TRECVID video summarization |
Full Paper |
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