Caverlee, James individual record
Professor - Term Appoint
Positions:
overview

My research is generally in the areas of web-scale information management, distributed data-intensive

systems, and social computing. Fundamentally, my overall research goal is to develop algorithms and

systems to enable efficient and trustworthy information sharing and knowledge discovery over dynamic,

heterogeneous, and massive-scale networked information systems.

education and training
selected publications
Academic Articles41
  • Wang, J., Ding, K., & Caverlee, J (2021). Sequential Recommendation for Cold-start Users with Meta Transitional Learning. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. abs/2107.06427, 1783-1787.
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  • Ding, K., Wang, J., Li, J., Caverlee, J., & Liu, H (2021). Weakly-supervised Graph Meta-learning for Few-shot Node Classification. CoRR. abs/2106.06873,
  • Wu, J., Nivargi, R., Lanka, S., Menon, A. M., Modukuri, S. A., Nakshatri, N., ... Giles, C. L (2021). Predicting the Reproducibility of Social and Behavioral Science Papers Using Supervised Learning Models. CoRR. abs/2104.04580,
  • Zhu, Z., Wang, J., & Caverlee, J (2021). Fairness-aware Personalized Ranking Recommendation via Adversarial Learning. CoRR. abs/2103.07849,
  • Liu, W., Zhang, Y., Wang, J., He, Y., Caverlee, J., Chan, P., Yeung, D. S., & Heng, P (2021). Item Relationship Graph Neural Networks for E-Commerce.. IEEE Trans Neural Netw Learn Syst. PP(99), 1-15.
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Chapters9
  • Wang, D. e., Webb, S., Lee, K., Caverlee, J., & Pu, C (2021). Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities. Encyclopedia of Complexity and Systems Science. 1-12. Springer Berlin Heidelberg.
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  • Caverlee, J., & Lee, K (2015). Weaponized Crowdsourcing: An Emerging Threat and Potential Countermeasures. Transparency in Social Media. 51-65. Springer International Publishing.
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  • Caverlee, J (2013). Exploitation in Human Computation Systems. Michelucci, P. (Eds.), Handbook of Human Computation. 837-845. Springer New York.
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  • Webb, S., Caverlee, J., & Pu, C (2012). Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities. Computational Complexity. 1433-1443. Springer New York.
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  • Caverlee, J (2009). Data Dictionary. Liu, L., & Özsu, M. T. (Eds.), Encyclopedia of Database Systems. 570-571. Springer US.
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Conference Papers143
  • Zhu, Z., He, Y., Zhao, X., & Caverlee, J (2021). Popularity Bias in Dynamic Recommendation. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2439-2449.
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  • Zhu, Z., Kim, J., Nguyen, T., Fenton, A., & Caverlee, J (2021). Fairness among New Items in Cold Start Recommender Systems. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. 767-776.
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  • Zhao, X., Zhu, Z., & Caverlee, J (2021). Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests. Proceedings of the Web Conference 2021, WWW '21: The Web Conference 2021. 888-899.
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  • Madanagopal, K., & Caverlee, J (2021). Towards Ongoing Detection of Linguistic Bias on Wikipedia. Companion Proceedings of the Web Conference 2021, WWW '21: The Web Conference 2021. 629-631.
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  • Zhu, Z., He, Y., Zhao, X., Zhang, Y., Wang, J., & Caverlee, J (2021). Popularity-Opportunity Bias in Collaborative Filtering. Proceedings of the 14th ACM International Conference on Web Search and Data Mining, WSDM '21: The Fourteenth ACM International Conference on Web Search and Data Mining. 85-93.
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chaired theses and dissertations
Email
caverlee@tamu.edu
First Name
James
Last Name
Caverlee
mailing address
Texas A&M University; Computer Science & Engineering; 3112 TAMU
College Station, TX 77843-3112
USA