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ORCIDJames Caverlee
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- affiliation: Texas A&M University
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2020 – today
- 2024
[j24]Kaize Ding
, Jianling Wang, Jundong Li, James Caverlee, Huan Liu:
Robust Graph Meta-Learning for Weakly Supervised Few-Shot Node Classification. ACM Trans. Knowl. Discov. Data 18(4): 83:1-83:18 (2024)- [c161]Takeshi Onishi, James Caverlee:
Political Bias of Large Language Models in Few-Shot News Summarization. BIAS 2024: 32-45 - [c160]Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng, Yuhe Ke, Wanxin Li, Lechao Cheng, Qingyu Chen, James Caverlee, Yutaka Matsuo, Irene Li:
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques. BioNLP@ACL 2024: 155-166 - [c159]Rohan Chaudhury, Maria Teleki, Xiangjue Dong, James Caverlee:
DACL: Disfluency Augmented Curriculum Learning for Fluent Text Generation. LREC/COLING 2024: 4311-4321 - [c158]Maria Teleki, Xiangjue Dong, James Caverlee:
Quantifying the Impact of Disfluency on Spoken Content Summarization. LREC/COLING 2024: 13419-13428 - [c157]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails in Vision-Language Models. CVPR 2024: 12988-12997 - [c156]Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee:
Federated Conversational Recommender Systems. ECIR (5) 2024: 50-65 - [c155]Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin, James Caverlee:
Countering Mainstream Bias via End-to-End Adaptive Local Learning. ECIR (5) 2024: 75-89 - [c154]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, James Caverlee, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Improving Data Efficiency for Recommenders and LLMs. RecSys 2024: 790-792 - [c153]Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee:
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. WWW (Companion Volume) 2024: 485-488 - [c152]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. WWW (Companion Volume) 2024: 726-729 - [i42]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails of Vision-Language Models. CoRR abs/2401.12425 (2024) - [i41]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng:
How to Train Data-Efficient LLMs. CoRR abs/2402.09668 (2024) - [i40]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Disclosure and Mitigation of Gender Bias in LLMs. CoRR abs/2402.11190 (2024) - [i39]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. CoRR abs/2402.11724 (2024) - [i38]Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu, James Caverlee:
Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models. CoRR abs/2403.03900 (2024) - [i37]Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng, Yuhe Ke, Wanxin Li, Lechao Cheng, Qingyu Chen, James Caverlee, Yutaka Matsuo, Irene Li:
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques. CoRR abs/2403.05881 (2024) - [i36]Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin, James Caverlee:
Countering Mainstream Bias via End-to-End Adaptive Local Learning. CoRR abs/2404.08887 (2024) - [i35]Chengkai Liu, Jianghao Lin, Hanzhou Liu, Jianling Wang, James Caverlee:
Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation. CoRR abs/2406.12580 (2024) - [i34]Zhuoer Wang, Leonardo F. R. Ribeiro, Alexandros Papangelis, Rohan Mukherjee, Tzu-Yen Wang, Xinyan Zhao, Arijit Biswas, James Caverlee, Angeliki Metallinou:
FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking. CoRR abs/2407.13945 (2024) - [i33]Chengkai Liu, Jianling Wang, James Caverlee:
TwinCL: A Twin Graph Contrastive Learning Model for Collaborative Filtering. CoRR abs/2409.19169 (2024) - 2023
- [c151]Xiangjue Dong, Yun He, Ziwei Zhu, James Caverlee:
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts. ACL (Findings) 2023: 10651-10666 - [c150]Karthic Madanagopal, James Caverlee:
Reinforced Sequence Training based Subjective Bias Correction. EACL 2023: 2577-2590 - [c149]Xiangjue Dong, Jiaying Lu, Jianling Wang, James Caverlee:
Closed-book Question Generation via Contrastive Learning. EACL 2023: 3142-3154 - [c148]Han Zhang, Ziwei Zhu, James Caverlee:
Evolution of Filter Bubbles and Polarization in News Recommendation. ECIR (2) 2023: 685-693 - [c147]Zhuoer Wang, Yicheng Wang, Ziwei Zhu, James Caverlee:
Unsupervised Candidate Answer Extraction through Differentiable Masker-Reconstructor Model. EMNLP (Findings) 2023: 5712-5723 - [c146]Xiangjue Dong, Ziwei Zhu, Zhuoer Wang, Maria Teleki, James Caverlee:
Co²PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning. EMNLP (Findings) 2023: 5859-5871 - [c145]Karthic Madanagopal, James Caverlee:
Bias Neutralization in Non-Parallel Texts: A Cyclic Approach with Auxiliary Guidance. EMNLP 2023: 14265-14278 - [c144]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD 2023: 5608-5617 - [c143]Mostafa Rahmani, James Caverlee, Fei Wang:
Incorporating Time in Sequential Recommendation Models. RecSys 2023: 784-790 - [c142]Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee:
Enhancing User Personalization in Conversational Recommenders. WWW 2023: 770-778 - [i32]Han Zhang, Ziwei Zhu, James Caverlee:
Evolution of Filter Bubbles and Polarization in News Recommendation. CoRR abs/2301.10926 (2023) - [i31]Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee:
Enhancing User Personalization in Conversational Recommenders. CoRR abs/2302.06656 (2023) - [i30]Yingqiang Ge, Mostafa Rahmani, Athirai A. Irissappane, Jose Sepulveda, James Caverlee, Fei Wang:
Automated Data Denoising for Recommendation. CoRR abs/2305.07070 (2023) - [i29]Xiangjue Dong, Yun He, Ziwei Zhu, James Caverlee:
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts. CoRR abs/2306.04535 (2023) - [i28]Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee:
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. CoRR abs/2308.15614 (2023) - [i27]Xiangjue Dong, Ziwei Zhu, Zhuoer Wang, Maria Teleki, James Caverlee:
Co$^2$PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning. CoRR abs/2310.12490 (2023) - [i26]Zhuoer Wang, Yicheng Wang, Ziwei Zhu, James Caverlee:
Unsupervised Candidate Answer Extraction through Differentiable Masker-Reconstructor Model. CoRR abs/2310.13106 (2023) - [i25]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation. CoRR abs/2311.00306 (2023) - [i24]Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu:
DALA: A Distribution-Aware LoRA-Based Adversarial Attack against Pre-trained Language Models. CoRR abs/2311.08598 (2023) - 2022
- [j23]Weiwen Liu, Yin Zhang, Jianling Wang, Yun He, James Caverlee, Patrick P. K. Chan, Daniel S. Yeung, Pheng-Ann Heng:
Item Relationship Graph Neural Networks for E-Commerce. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4785-4799 (2022) - [c141]Kaize Ding, Jianling Wang, James Caverlee, Huan Liu:
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. AAAI 2022: 6524-6531 - [c140]Zhuoer Wang, Qizhang Feng, Mohinish Chatterjee, Xing Zhao, Yezi Liu, Yuening Li, Abhay Kumar Singh, Frank M. Shipman, Xia Hu, James Caverlee:
RES: An Interpretable Replicability Estimation System for Research Publications. AAAI 2022: 13230-13232 - [c139]Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee:
Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems. CIKM 2022: 1238-1247 - [c138]Ziwei Zhu, James Caverlee:
Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning. WSDM 2022: 1497-1506 - [c137]Karthic Madanagopal, James Caverlee:
Improving Linguistic Bias Detection in Wikipedia using Cross-Domain Adaptive Pre-Training. WWW (Companion Volume) 2022: 1301-1309 - [c136]Yun He, Xue Feng, Cheng Cheng, Geng Ji, Yunsong Guo, James Caverlee:
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. WWW 2022: 2205-2215 - [i23]Yun He, Xue Feng, Cheng Cheng, Geng Ji, Yunsong Guo, James Caverlee:
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. CoRR abs/2203.06801 (2022) - [i22]Ziwei Zhu, Yun He, Xing Zhao, James Caverlee:
Evolution of Popularity Bias: Empirical Study and Debiasing. CoRR abs/2207.03372 (2022) - [i21]Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee:
Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems. CoRR abs/2208.03298 (2022) - [i20]Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee:
Towards Fair Conversational Recommender Systems. CoRR abs/2208.03854 (2022) - [i19]Xiangjue Dong, Jiaying Lu, Jianling Wang, James Caverlee:
Closed-book Question Generation via Contrastive Learning. CoRR abs/2210.06781 (2022) - [i18]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR abs/2210.14309 (2022) - 2021
- [c135]Yin Zhang, Yun He, James Caverlee:
Vibe check: social resonance learning for enhanced recommendation. ASONAM 2021: 164-167 - [c134]Ziwei Zhu, Yun He, Xing Zhao, James Caverlee:
Popularity Bias in Dynamic Recommendation. KDD 2021: 2439-2449 - [c133]Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee:
Session-based Recommendation with Hypergraph Attention Networks. SDM 2021: 82-90 - [c132]Ziwei Zhu, Jingu Kim, Trung Nguyen, Aish Fenton, James Caverlee:
Fairness among New Items in Cold Start Recommender Systems. SIGIR 2021: 767-776 - [c131]Jianling Wang, Kaize Ding, James Caverlee:
Sequential Recommendation for Cold-start Users with Meta Transitional Learning. SIGIR 2021: 1783-1787 - [c130]Ziwei Zhu, Yun He, Xing Zhao, Yin Zhang, Jianling Wang, James Caverlee:
Popularity-Opportunity Bias in Collaborative Filtering. WSDM 2021: 85-93 - [c129]Karthic Madanagopal, James Caverlee:
Towards Ongoing Detection of Linguistic Bias on Wikipedia. WWW (Companion Volume) 2021: 629-631 - [c128]Xing Zhao, Ziwei Zhu, James Caverlee:
Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests. WWW 2021: 888-899 - [i17]Ziwei Zhu, Jianling Wang, James Caverlee:
Fairness-aware Personalized Ranking Recommendation via Adversarial Learning. CoRR abs/2103.07849 (2021) - [i16]Jian Wu, Rajal Nivargi, Sree Sai Teja Lanka, Arjun Manoj Menon, Sai Ajay Modukuri, Nishanth Nakshatri, Xin Wei, Zhuoer Wang, James Caverlee, Sarah Michele Rajtmajer, C. Lee Giles:
Predicting the Reproducibility of Social and Behavioral Science Papers Using Supervised Learning Models. CoRR abs/2104.04580 (2021) - [i15]Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu:
Weakly-supervised Graph Meta-learning for Few-shot Node Classification. CoRR abs/2106.06873 (2021) - [i14]Monika Daryani, James Caverlee:
Identifying Hijacked Reviews. CoRR abs/2107.05385 (2021) - [i13]Jianling Wang, Kaize Ding, James Caverlee:
Sequential Recommendation for Cold-start Users with Meta Transitional Learning. CoRR abs/2107.06427 (2021) - [i12]Kaize Ding, Jianling Wang, James Caverlee, Huan Liu:
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. CoRR abs/2112.09810 (2021) - [i11]Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee:
Session-based Recommendation with Hypergraph Attention Networks. CoRR abs/2112.14266 (2021) - 2020
- [c127]Parisa Kaghazgaran, James Caverlee:
Towards an Automated Writing Assistant for Online Reviews. AutomationXP@CHI 2020 - [c126]Jianling Wang, James Caverlee:
Recommending Music Curators: A Neural Style-Aware Approach. ECIR (1) 2020: 191-204 - [c125]Yun He, Ziwei Zhu, Yin Zhang, Qin Chen, James Caverlee:
Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition. EMNLP (1) 2020: 4604-4614 - [c124]Yun He, Zhuoer Wang, Yin Zhang, Ruihong Huang, James Caverlee:
PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. EMNLP (1) 2020: 7572-7582 - [c123]Yin Zhang, Ziwei Zhu, Yun He, James Caverlee:
Content-Collaborative Disentanglement Representation Learning for Enhanced Recommendation. RecSys 2020: 43-52 - [c122]Ziwei Zhu, Yun He, Yin Zhang, James Caverlee:
Unbiased Implicit Recommendation and Propensity Estimation via Combinational Joint Learning. RecSys 2020: 551-556 - [c121]Ziwei Zhu, Jianling Wang, James Caverlee:
Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems. SIGIR 2020: 449-458 - [c120]Parisa Kaghazgaran, Jianling Wang, Ruihong Huang, James Caverlee:
ADORE: Aspect Dependent Online REview Labeling for Review Generation. SIGIR 2020: 1021-1030 - [c119]Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, James Caverlee:
Next-item Recommendation with Sequential Hypergraphs. SIGIR 2020: 1101-1110 - [c118]Ziwei Zhu, Shahin Sefati, Parsa Saadatpanah, James Caverlee:
Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation. SIGIR 2020: 1121-1130 - [c117]Yun He, Yin Zhang, Weiwen Liu, James Caverlee:
Consistency-Aware Recommendation for User-Generated Item List Continuation. WSDM 2020: 250-258 - [c116]Jianling Wang, Ziwei Zhu, James Caverlee:
User Recommendation in Content Curation Platforms. WSDM 2020: 627-635 - [c115]Jianling Wang, Kaize Ding, Ziwei Zhu, Yin Zhang, James Caverlee:
Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion. WSDM 2020: 636-644 - [c114]Jianling Wang, Raphael Louca, Diane Hu, Caitlin Cellier, James Caverlee, Liangjie Hong:
Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce. WSDM 2020: 645-653 - [c113]Xing Zhao, Ziwei Zhu, Yin Zhang, James Caverlee:
Improving the Estimation of Tail Ratings in Recommender System with Multi-Latent Representations. WSDM 2020: 762-770 - [c112]Xing Zhao, Ziwei Zhu, Majid Alfifi, James Caverlee:
Addressing the Target Customer Distortion Problem in Recommender Systems. WWW 2020: 2969-2975 - [c111]Yin Zhang, Yun He, Jianling Wang, James Caverlee:
Adaptive Hierarchical Translation-based Sequential Recommendation. WWW 2020: 2984-2990 - [e5]James Caverlee, Xia (Ben) Hu, Mounia Lalmas, Wei Wang:
WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020. ACM 2020, ISBN 978-1-4503-6822-3 [contents] - [i10]Habeeb Hooshmand, James Caverlee:
Understanding Car-Speak: Replacing Humans in Dealerships. CoRR abs/2002.02070 (2020) - [i9]Yun He, Zhuoer Wang, Yin Zhang, Ruihong Huang, James Caverlee:
PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. CoRR abs/2010.03725 (2020) - [i8]Yun He, Ziwei Zhu, Yin Zhang, Qin Chen, James Caverlee:
Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition. CoRR abs/2010.03746 (2020)
2010 – 2019
- 2019
- [j22]Qingquan Song, Hancheng Ge, James Caverlee, Xia Hu:
Tensor Completion Algorithms in Big Data Analytics. ACM Trans. Knowl. Discov. Data 13(1): 6:1-6:48 (2019) - [c110]Parisa Kaghazgaran, Majid Alfifi, James Caverlee:
Wide-Ranging Review Manipulation Attacks: Model, Empirical Study, and Countermeasures. CIKM 2019: 981-990 - [c109]Yun He, Jianling Wang, Wei Niu, James Caverlee:
A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists. CIKM 2019: 1481-1490 - [c108]Yin Zhang, James Caverlee:
Instagrammers, Fashionistas, and Me: Recurrent Fashion Recommendation with Implicit Visual Influence. CIKM 2019: 1583-1592 - [c107]Majid Alfifi, Parisa Kaghazgaran, James Caverlee, Fred Morstatter:
A Large-Scale Study of ISIS Social Media Strategy: Community Size, Collective Influence, and Behavioral Impact. ICWSM 2019: 58-67 - [c106]Parisa Kaghazgaran, Majid Alfifi, James Caverlee:
TOmCAT: Target-Oriented Crowd Review Attacks and Countermeasures. ICWSM 2019: 302-312 - [c105]Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu:
An Interpretable Neural Model with Interactive Stepwise Influence. PAKDD (3) 2019: 528-540 - [c104]Jianling Wang, James Caverlee:
Recurrent Recommendation with Local Coherence. WSDM 2019: 564-572 - [c103]Ziwei Zhu, Jianling Wang, James Caverlee:
Improving Top-K Recommendation via JointCollaborative Autoencoders. WWW 2019: 3483-3482 - [i7]Yun He, Haochen Chen, Ziwei Zhu, James Caverlee:
Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation. CoRR abs/1901.00597 (2019) - [i6]Yun He, Jianling Wang, Wei Niu, James Caverlee:
A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists. CoRR abs/1912.13023 (2019) - [i5]Yun He, Yin Zhang, Weiwen Liu, James Caverlee:
Consistency-Aware Recommendation for User-Generated ItemList Continuation. CoRR abs/1912.13031 (2019) - 2018
- [j21]Benjamin A. Knott, Jonathan Gratch, Angelo Cangelosi, James Caverlee:
ACM Transactions on Interactive Intelligent Systems (TiiS) Special Issue on Trust and Influence in Intelligent Human-Machine Interaction. ACM Trans. Interact. Intell. Syst. 8(4): 25:1-25:3 (2018) - [j20]Victor Bahl, Barbara Carminati, James Caverlee, Ing-Ray Chen, Wynne Hsu, Toru Ishida, Valérie Issarny, Surya Nepal, Indrakshi Ray, Kui Ren, Shamik Sural, Mei-Ling Shyu:
Editorial. IEEE Trans. Serv. Comput. 11(1): 1-4 (2018) - [c102]Wei Niu, James Caverlee, Haokai Lu:
Location-Sensitive User Profiling Using Crowdsourced Labels. AAAI 2018: 386-393 - [c101]Chenxi Qiu, Anna Cinzia Squicciarini, Dev Rishi Khare, Barbara Carminati, James Caverlee:
CrowdEval: A Cost-Efficient Strategy to Evaluate Crowdsourced Worker's Reliability. AAMAS 2018: 1486-1494 - [c100]Ziwei Zhu, Xia Hu, James Caverlee:
Fairness-Aware Tensor-Based Recommendation. CIKM 2018: 1153-1162 - [c99]Cheng Cao, Zhengzhang Chen, James Caverlee, Lu-An Tang, Chen Luo, Zhichun Li:
Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks. CIKM 2018: 1977-1985 - [c98]Hancheng Ge, Kai Zhang, Majid Alfifi, Xia Hu, James Caverlee:
DisTenC: A Distributed Algorithm for Scalable Tensor Completion on Spark. ICDE 2018: 137-148 - [c97]Yun He, Haochen Chen, Ziwei Zhu, James Caverlee:
Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation. ICDM 2018: 1025-1030 - [c96]Xing Zhao, Qingquan Song, James Caverlee, Xia Hu:
TrailMix: An Ensemble Recommender System for Playlist Curation and Continuation. RecSys Challenge 2018: 8:1-8:6 - [c95]Yin Zhang, Haokai Lu, Wei Niu, James Caverlee:
Quality-aware neural complementary item recommendation. RecSys 2018: 77-85 - [c94]Haokai Lu, Wei Niu, James Caverlee:
Learning Geo-Social User Topical Profiles with Bayesian Hierarchical User Factorization. SIGIR 2018: 205-214 - [c93]Xing Zhao, James Caverlee:
Vitriol on Social Media: Curation and Investigation. SocInfo (1) 2018: 487-504 - [c92]Parisa Kaghazgaran, James Caverlee, Anna Cinzia Squicciarini:
Combating Crowdsourced Review Manipulators: A Neighborhood-Based Approach. WSDM 2018: 306-314 - [c91]Wei Niu, James Caverlee, Haokai Lu:
Neural Personalized Ranking for Image Recommendation. WSDM 2018: 423-431 - [r9]James Caverlee:
Data Dictionary. Encyclopedia of Database Systems (2nd ed.) 2018 - [r8]James Caverlee:
Topic Maps. Encyclopedia of Database Systems (2nd ed.) 2018 - [r7]James Caverlee, Prasenjit Mitra, Mary Lynette Larsgaard:
Dublin Core. Encyclopedia of Database Systems (2nd ed.) 2018 - [r6]James Caverlee, Zhiyuan Cheng:
Geography and Web Communities. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i4]Ziwei Zhu, Jianling Wang, Yin Zhang, James Caverlee:
Fairness-Aware Recommendation of Information Curators. CoRR abs/1809.03040 (2018) - 2017
- [c90]Chenxi Qiu, Anna Cinzia Squicciarini, Sarah Michele Rajtmajer, James Caverlee:
Dynamic Contract Design for Heterogenous Workers in Crowdsourcing for Quality Control. ICDCS 2017: 1168-1177 - [c89]Parisa Kaghazgaran, James Caverlee, Majid Alfifi:
Behavioral Analysis of Review Fraud: Linking Malicious Crowdsourcing to Amazon and Beyond. ICWSM 2017: 560-563 - [c88]Qingquan Song, Xiao Huang, Hancheng Ge, James Caverlee, Xia Hu:
Multi-Aspect Streaming Tensor Completion. KDD 2017: 435-443 - [c87]Wenlin Yao, Zeyu Dai, Ruihong Huang, James Caverlee:
Online Deception Detection Refueled by Real World Data Collection. RANLP 2017: 793-802 - [c86]Cheng Cao, Hancheng Ge, Haokai Lu, Xia Hu, James Caverlee:
What Are You Known For?: Learning User Topical Profiles with Implicit and Explicit Footprints. SIGIR 2017: 743-752 - [c85]Shanshan Li, James Caverlee, Wei Niu, Parisa Kaghazgaran:
Crowdsourced App Review Manipulation. SIGIR 2017: 1137-1140 - [c84]Majid Alfifi, James Caverlee:
Badly Evolved? Exploring Long-Surviving Suspicious Users on Twitter. SocInfo (1) 2017: 218-233 - [i3]Wenlin Yao, Zeyu Dai, Ruihong Huang, James Caverlee:
Online Deception Detection Refueled by Real World Data Collection. CoRR abs/1707.09406 (2017) - [i2]Qingquan Song, Hancheng Ge, James Caverlee, Xia Hu:
Tensor Completion Algorithms in Big Data Analytics. CoRR abs/1711.10105 (2017) - 2016
- [j19]Wei Niu, Zhijiao Liu, James Caverlee:
On Local Expert Discovery via Geo-Located Crowds, Queries, and Candidates. ACM Trans. Spatial Algorithms Syst. 2(4): 14:1-14:24 (2016) - [c83]Hancheng Ge, James Caverlee:
College Towns, Vacation Spots, and Tech Hubs: Using Geo-Social Media to Model and Compare Locations. AAAI 2016: 129-136 - [c82]Wei Niu, James Caverlee, Haokai Lu, Krishna Yeswanth Kamath:
Community-based geospatial tag estimation. ASONAM 2016: 279-286 - [c81]Chenxi Qiu, Anna Cinzia Squicciarini, Barbara Carminati, James Caverlee, Dev Rishi Khare:
CrowdSelect: Increasing Accuracy of Crowdsourcing Tasks through Behavior Prediction and User Selection. CIKM 2016: 539-548 - [c80]Hancheng Ge, James Caverlee, Nan Zhang, Anna Cinzia Squicciarini:
Uncovering the Spatio-Temporal Dynamics of Memes in the Presence of Incomplete Information. CIKM 2016: 1493-1502 - [c79]Wei Niu, Zhijiao Liu, James Caverlee:
LExL: A Learning Approach for Local Expert Discovery on Twitter. ECIR 2016: 803-809 - [c78]Haokai Lu, James Caverlee, Wei Niu:
Discovering What You're Known For: A Contextual Poisson Factorization Approach. RecSys 2016: 253-260 - [c77]Hancheng Ge, James Caverlee, Haokai Lu:
TAPER: A Contextual Tensor-Based Approach for Personalized Expert Recommendation. RecSys 2016: 261-268 - [e4]Ravi Kumar, James Caverlee, Hanghang Tong:
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, CA, USA, August 18-21, 2016. IEEE Computer Society 2016, ISBN 978-1-5090-2846-7 [contents] - 2015
- [c76]Haokai Lu, James Caverlee, Wei Niu:
BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media. CIKM 2015: 213-222 - [c75]Cheng Cao, James Caverlee, Kyumin Lee, Hancheng Ge, Jin-Wook Chung:
Organic or Organized?: Exploring URL Sharing Behavior. CIKM 2015: 513-522 - [c74]Yuan Liang, James Caverlee, Cheng Cao:
A Noise-Filtering Approach for Spatio-temporal Event Detection in Social Media. ECIR 2015: 233-244 - [c73]Cheng Cao, James Caverlee:
Detecting Spam URLs in Social Media via Behavioral Analysis. ECIR 2015: 703-714 - [c72]Hancheng Ge, James Caverlee, Kyumin Lee:
Crowds, Gigs, and Super Sellers: A Measurement Study of a Supply-Driven Crowdsourcing Marketplace. ICWSM 2015: 120-129 - [c71]Haokai Lu, James Caverlee:
Exploiting Geo-Spatial Preference for Personalized Expert Recommendation. RecSys 2015: 67-74 - [c70]Amir Fayazi, Kyumin Lee, James Caverlee, Anna Cinzia Squicciarini:
Uncovering Crowdsourced Manipulation of Online Reviews. SIGIR 2015: 233-242 - [c69]Klaus Berberich, James Caverlee, Miles Efron, Claudia Hauff, Vanessa Murdock, Milad Shokouhi, Bart Thomee:
SIGIR 2015 Workshop on Temporal, Social and Spatially-aware Information Access (#TAIA2015). SIGIR 2015: 1149-1150 - [c68]Natwar Modani, Elham Khabiri, Harini Srinivasan, James Caverlee:
Creating Diverse Product Review Summaries: A Graph Approach. WISE (1) 2015: 169-184 - 2014
- [j18]Adam Jatowt, Carlos Castillo, James Caverlee, Katsumi Tanaka:
Report on the WebQuality 2014 Workshop. SIGIR Forum 48(2): 93-95 (2014) - [c67]Cheng Cao, James Caverlee:
Behavioral detection of spam URL sharing: Posting patterns versus click patterns. ASONAM 2014: 138-141 - [c66]Jalal Mahmud, Jeffrey Nichols, Michelle X. Zhou, James Caverlee, Yi Zeng, Liang Chen, John O'Donovan:
DUBMOD14 - International Workshop on Data-driven User Behavioral Modeling and Mining from Social Media. CIKM 2014: 2092-2093 - [c65]Zhiyuan Cheng, James Caverlee, Himanshu Barthwal, Vandana Bachani:
Who is the barbecue king of texas?: a geo-spatial approach to finding local experts on twitter. SIGIR 2014: 335-344 - [c64]Kyumin Lee, James Caverlee, Calton Pu:
Social spam, campaigns, misinformation and crowdturfing. WWW (Companion Volume) 2014: 199-200 - [c63]Zhiyuan Cheng, James Caverlee, Himanshu Barthwal, Vandana Bachani:
Finding local experts on twitter. WWW (Companion Volume) 2014: 241-242 - [e3]Jalal Mahmud, James Caverlee, Jeffrey Nichols, John O'Donovan, Michelle X. Zhou, Yi Zeng, Liang Chen:
Proceedings of the 3rd Workshop on Data-Driven User Behavioral Modeling and Mining from Social Media, DUBMOD@CIKM 2014, Shanghai, China, November 3, 2014. ACM 2014, ISBN 978-1-4503-1303-2 [contents] - 2013
- [j17]James Caverlee, Zhiyuan Cheng, Daniel Z. Sui, Krishna Yeswanth Kamath:
Towards Geo-Social Intelligence: Mining, Analyzing, and Leveraging Geospatial Footprints in Social Media. IEEE Data Eng. Bull. 36(3): 33-41 (2013) - [j16]James Caverlee, Calton Pu, Dimitrios Georgakopoulos, James Joshi:
Editorial for CollaborateCom 2011 Special Issue. Mob. Networks Appl. 18(2): 235-236 (2013) - [j15]Zhiyuan Cheng, James Caverlee, Kyumin Lee:
A content-driven framework for geolocating microblog users. ACM Trans. Intell. Syst. Technol. 4(1): 2:1-2:27 (2013) - [j14]Kyumin Lee, James Caverlee, Zhiyuan Cheng, Daniel Z. Sui:
Campaign extraction from social media. ACM Trans. Intell. Syst. Technol. 5(1): 9:1-9:28 (2013) - [c62]Jeffrey McGee, James Caverlee, Zhiyuan Cheng:
Location prediction in social media based on tie strength. CIKM 2013: 459-468 - [c61]Krishna Yeswanth Kamath, James Caverlee:
Spatio-temporal meme prediction: learning what hashtags will be popular where. CIKM 2013: 1341-1350 - [c60]Jalal Mahmud, Jeffrey Nichols, Michelle X. Zhou, James Caverlee, John O'Donovan:
DUBMOD13: international workshop on data-driven user behavioral modelling and mining from social media. CIKM 2013: 2551-2552 - [c59]Yuan Liang, James Caverlee, Zhiyuan Cheng, Krishna Yeswanth Kamath:
How big is the crowd?: event and location based population modeling in social media. HT 2013: 99-108 - [c58]Kyumin Lee, Krishna Yeswanth Kamath, James Caverlee:
Combating Threats to Collective Attention in Social Media: An Evaluation. ICWSM 2013 - [c57]Kyumin Lee, Prithivi Tamilarasan, James Caverlee:
Crowdturfers, Campaigns, and Social Media: Tracking and Revealing Crowdsourced Manipulation of Social Media. ICWSM 2013 - [c56]Krishna Yeswanth Kamath, Ana-Maria Popescu, James Caverlee:
Board Recommendation in Pinterest. UMAP Workshops 2013 - [c55]Ana-Maria Popescu, Krishna Yeswanth Kamath, James Caverlee:
Mining Potential Domain Expertise in Pinterest. UMAP Workshops 2013 - [c54]Krishna Yeswanth Kamath, Ana-Maria Popescu, James Caverlee:
Board coherence in Pinterest: non-visual aspects of a visual site. WWW (Companion Volume) 2013: 49-50 - [c53]Krishna Yeswanth Kamath, James Caverlee, Kyumin Lee, Zhiyuan Cheng:
Spatio-temporal dynamics of online memes: a study of geo-tagged tweets. WWW 2013: 667-678 - [c52]Yuan Liang, James Caverlee, John Mander:
Text vs. images: on the viability of social media to assess earthquake damage. WWW (Companion Volume) 2013: 1003-1006 - [e2]Jalal Mahmud, James Caverlee, Jeffrey Nichols, John O'Donovan, Michelle X. Zhou:
Proceedings of the 2013 Workshop on Data-Driven User Behavioral Modelling and Mining from Social Media, DUBMOD@CIKM 2013 San Francisco, CA, USA, October 28, 2013. ACM 2013, ISBN 978-1-4503-2417-5 [contents] - [r5]James Caverlee:
Exploitation in Human Computation Systems. Handbook of Human Computation 2013: 837-845 - 2012
- [j13]Said Kashoob, James Caverlee:
Temporal dynamics of communities in social bookmarking systems. Soc. Netw. Anal. Min. 2(4): 387-404 (2012) - [j12]Chiao-Fang Hsu, James Caverlee, Elham Khabiri:
Predicting community preference of comments on the Social Web. Web Intell. Agent Syst. 10(4): 447-463 (2012) - [c51]Krishna Yeswanth Kamath, James Caverlee:
Content-based crowd retrieval on the real-time web. CIKM 2012: 195-204 - [c50]Krishna Yeswanth Kamath, James Caverlee, Zhiyuan Cheng, Daniel Z. Sui:
Spatial influence vs. community influence: modeling the global spread of social media. CIKM 2012: 962-971 - [c49]Jalal Mahmud, James Caverlee, Jeffrey Nichols, John O'Donovan, Michelle X. Zhou:
DUBMMSM'12: international workshop on data-driven user behavioral modeling and mining from social media. CIKM 2012: 2752-2753 - [c48]James Caverlee, Zhiyuan Cheng, Wai Gen Yee, Roger Liew, Yuan Liang:
Public checkins versus private queries: measuring and evaluating spatial preference. LBSN@GIS 2012: 40-47 - [c47]Elham Khabiri, James Caverlee, Krishna Yeswanth Kamath:
Predicting semantic annotations on the real-time web. HT 2012: 219-228 - [c46]Kyumin Lee, James Caverlee, Krishna Yeswanth Kamath, Zhiyuan Cheng:
Detecting collective attention spam. WebQuality@WWW 2012: 48-55 - [e1]Jalal Mahmud, James Caverlee, Jeffrey Nichols, John O'Donovan, Michelle X. Zhou:
Proceedings of the 2012 workshop on Data-driven User Behavioral Modelling and Mining from Social Media, DUBMMSM 2012, October 29, 2012, Maui, Hawaii, USA. ACM 2012, ISBN 978-1-4503-1707-8 [contents] - 2011
- [c45]Kyumin Lee, James Caverlee, Zhiyuan Cheng, Daniel Z. Sui:
Content-driven detection of campaigns in social media. CIKM 2011: 551-556 - [c44]Zhiyuan Cheng, James Caverlee, Krishna Yeswanth Kamath, Kyumin Lee:
Toward traffic-driven location-based web search. CIKM 2011: 805-814 - [c43]Krishna Yeswanth Kamath, James Caverlee:
Discovering trending phrases on information streams. CIKM 2011: 2245-2248 - [c42]Jeffrey McGee, James Caverlee, Zhiyuan Cheng:
A geographic study of tie strength in social media. CIKM 2011: 2333-2336 - [c41]Zhiyuan Cheng, James Caverlee, Kyumin Lee, Daniel Z. Sui:
Exploring Millions of Footprints in Location Sharing Services. ICWSM 2011 - [c40]Elham Khabiri, James Caverlee, Chiao-Fang Hsu:
Summarizing User-Contributed Comments. ICWSM 2011 - [c39]Kyumin Lee, Brian David Eoff, James Caverlee:
Seven Months with the Devils: A Long-Term Study of Content Polluters on Twitter. ICWSM 2011 - [c38]Chiao-Fang Hsu, James Caverlee, Elham Khabiri:
Hierarchical comments-based clustering. SAC 2011: 1130-1137 - [c37]James Caverlee, Zhiyuan Cheng, Brian Eoff, Chiao-Fang Hsu, Krishna Yeswanth Kamath, Jeffrey McGee:
CrowdTracker: enabling community-based real-time web monitoring. SIGIR 2011: 1283-1284 - [c36]Krishna Yeswanth Kamath, James Caverlee:
Expert-Driven Topical Classification of Short Message Streams. SocialCom/PASSAT 2011: 388-393 - [c35]Krishna Yeswanth Kamath, James Caverlee:
Transient crowd discovery on the real-time social web. WSDM 2011: 585-594 - 2010
- [j11]James Caverlee, Ling Liu, Steve Webb:
The SocialTrust framework for trusted social information management: Architecture and algorithms. Inf. Sci. 180(1): 95-112 (2010) - [c34]Zhiyuan Cheng, James Caverlee, Kyumin Lee:
You are where you tweet: a content-based approach to geo-locating twitter users. CIKM 2010: 759-768 - [c33]Krishna Yeswanth Kamath, James Caverlee:
Identifying hotspots on the real-time web. CIKM 2010: 1837-1840 - [c32]James Caverlee, Zhiyuan Cheng, Brian Eoff, Chiao-Fang Hsu, Krishna Yeswanth Kamath, Said Kashoob, Jeremy Kelley, Elham Khabiri, Kyumin Lee:
SocialTrust++: Building community-based trust in Social Information Systems. CollaborateCom 2010: 1-7 - [c31]Steve Webb, James Caverlee, Calton Pu:
A Summary of Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities. GrC 2010: 39-40 - [c30]Said Kashoob, James Caverlee, Krishna Yeswanth Kamath:
Community-based ranking of the social web. HT 2010: 141-150 - [c29]Kyumin Lee, Brian David Eoff, James Caverlee:
Devils, Angels, and Robots: Tempting Destructive Users in Social Media. ICWSM 2010 - [c28]Kyumin Lee, James Caverlee, Steve Webb:
Uncovering social spammers: social honeypots + machine learning. SIGIR 2010: 435-442 - [c27]Kyumin Lee, James Caverlee, Steve Webb:
The social honeypot project: protecting online communities from spammers. WWW 2010: 1139-1140 - [i1]Ying Ding, Erjia Yan, Arthur R. Frazho, James Caverlee:
PageRank for ranking authors in co-citation networks. CoRR abs/1012.4872 (2010)
2000 – 2009
- 2009
- [j10]Ying Ding, Elin K. Jacob, James Caverlee, Michael A. H. Fried, Zhixiong Zhang:
Profiling Social Networks: A Social Tagging Perspective. D Lib Mag. 15(3/4) (2009) - [j9]Ying Ding, Erjia Yan, Arthur R. Frazho, James Caverlee:
PageRank for ranking authors in co-citation networks. J. Assoc. Inf. Sci. Technol. 60(11): 2229-2243 (2009) - [j8]James Caverlee, Steve Webb, Ling Liu, William B. Rouse:
A Parameterized Approach to Spam-Resilient Link Analysis of the Web. IEEE Trans. Parallel Distributed Syst. 20(10): 1422-1438 (2009) - [c26]Said Kashoob, James Caverlee, Elham Khabiri:
Probabilistic Generative Models of the Social Annotation Process. CSE (4) 2009: 42-49 - [c25]Chiao-Fang Hsu, Elham Khabiri, James Caverlee:
Ranking Comments on the Social Web. CSE (4) 2009: 90-97 - [c24]Said Kashoob, James Caverlee, Ying Ding:
A Categorical Model for Discovering Latent Structure in Social Annotations. ICWSM 2009 - [c23]Elham Khabiri, Chiao-Fang Hsu, James Caverlee:
Analyzing and Predicting Community Preference of Socially Generated Metadata: A Case Study on Comments in the Digg Community. ICWSM 2009 - [r4]Steve Webb, James Caverlee, Calton Pu:
Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities. Encyclopedia of Complexity and Systems Science 2009: 4367-4378 - [r3]James Caverlee:
Data Dictionary. Encyclopedia of Database Systems 2009: 570-571 - [r2]James Caverlee, Prasenjit Mitra, Mary Laarsgard:
Dublin Core. Encyclopedia of Database Systems 2009: 949 - [r1]James Caverlee:
Topic Maps. Encyclopedia of Database Systems 2009: 3124-3126 - 2008
- [c22]Steve Webb, James Caverlee, Calton Pu:
Social Honeypots: Making Friends With A Spammer Near You. CEAS 2008 - [c21]Steve Webb, James Caverlee, Calton Pu:
Predicting web spam with HTTP session information. CIKM 2008: 339-348 - [c20]James Caverlee, Steve Webb:
A Large-Scale Study of MySpace: Observations and Implications for Online Social Networks. ICWSM 2008 - [c19]James Caverlee, Ling Liu, Steve Webb:
Socialtrust: tamper-resilient trust establishment in online communities. JCDL 2008: 104-114 - [c18]Robert Graham, James Caverlee:
Exploring Feedback Models in Interactive Tagging. Web Intelligence 2008: 141-147 - [c17]James Caverlee, Ling Liu, Steve Webb:
Towards robust trust establishment in web-based social networks with socialtrust. WWW 2008: 1163-1164 - [c16]Robert Graham, Brian Eoff, James Caverlee:
Plurality: a context-aware personalized tagging system. WWW 2008: 1165-1166 - 2007
- [j7]James Caverlee, Joonsoo Bae, Qinyi Wu, Ling Liu, Calton Pu, William B. Rouse:
Workflow management for enterprise transformation. Inf. Knowl. Syst. Manag. 6(1-2): 61-80 (2007) - [j6]Daniel Rocco, James Caverlee, Ling Liu, Terence Critchlow:
Service Class Driven Dynamic Data Source Discovery with DynaBot. Int. J. Web Serv. Res. 4(3): 26-48 (2007) - [j5]Joonsoo Bae, Ling Liu, James Caverlee, Liang-Jie Zhang, Hyerim Bae:
Development of Distance Measures for Process Mining, Discovery and Integration. Int. J. Web Serv. Res. 4(4): 1-17 (2007) - [c15]Steve Webb, James Caverlee, Calton Pu:
Characterizing Web Spam Using Content and HTTP Session Analysis. CEAS 2007 - [c14]Bhuvan Bamba, Ling Liu, James Caverlee, Vaibhav Padliya, Mudhakar Srivatsa, Tushar Bansal, Mahesh Palekar, Joseph Patrao, Suiyang Li, Aameek Singh:
DSphere: A Source-Centric Approach to Crawling, Indexing and Searching the World Wide Web. ICDE 2007: 1515-1516 - [c13]James Caverlee, Steve Webb, Ling Liu:
Spam-Resilient Web Rankings via Influence Throttling. IPDPS 2007: 1-10 - [c12]James Caverlee, Ling Liu:
Countering web spam with credibility-based link analysis. PODC 2007: 157-166 - 2006
- [j4]Ling Liu, Jianjun Zhang, Wei Han, Calton Pu, James Caverlee, Sungkeun Park, Terence Critchlow, David Buttler, Matthew Coleman:
XWRAPComposer: A Multi-Page Data Extraction Service. Int. J. Web Serv. Res. 3(2): 33-60 (2006) - [j3]James Caverlee, Ling Liu, Daniel Rocco:
Discovering Interesting Relationships among Deep Web Databases: A Source-Biased Approach. World Wide Web 9(4): 585-622 (2006) - [c11]Joonsoo Bae, James Caverlee, Ling Liu, Hua Yan:
Process Mining by Measuring Process Block Similarity. Business Process Management Workshops 2006: 141-152 - [c10]Steve Webb, James Caverlee, Calton Pu:
Introducing the Webb Spam Corpus: Using Email Spam to Identify Web Spam Automatically. CEAS 2006 - [c9]James Caverlee, Ling Liu, William B. Rouse:
Link-Based Ranking of the Web with Source-Centric Collaboration. CollaborateCom 2006 - [c8]Joonsoo Bae, Ling Liu, James Caverlee, William B. Rouse:
Process Mining, Discovery, and Integration using Distance Measures. ICWS 2006: 479-488 - [c7]James Caverlee, Ling Liu, Joonsoo Bae:
Distributed query sampling: a quality-conscious approach. SIGIR 2006: 340-347 - 2005
- [j2]Ling Liu, David Buttler, James Caverlee, Calton Pu, Jianjun Zhang:
A methodical approach to extracting interesting objects from dynamic web pages. Int. J. Web Grid Serv. 1(2): 165-195 (2005) - [j1]James Caverlee, Ling Liu:
QA-Pagelet: Data Preparation Techniques for Large-Scale Data Analysis of the Deep Web. IEEE Trans. Knowl. Data Eng. 17(9): 1247-1262 (2005) - [c6]Ling Liu, Jianjun Zhang, Wei Han, Calton Pu, James Caverlee, Sungkeun Park, Terence Critchlow, Matthew Coleman, David Buttler:
XWRAPComposer: A Multi-Page Data Extraction Service for Bio-Computing Applications. IEEE SCC 2005: 271-278 - [c5]Daniel Rocco, James Caverlee, Ling Liu, Terence Critchlow:
Domain-Specific Web Service Discovery with Service Class Descriptions. ICWS 2005: 481-488 - [c4]Daniel Rocco, James Caverlee, Ling Liu:
XPACK: A High-Performance WEB Document Encoding. WEBIST 2005: 32-39 - [c3]Daniel Rocco, James Caverlee, Ling Liu, Terence Critchlow:
Exploiting the deep web with DynaBot: matching, probing, and ranking. WWW (Special interest tracks and posters) 2005: 1174-1175 - 2004
- [c2]James Caverlee, Ling Liu, David Buttler:
Probe, Cluster, and Discover: Focused Extraction of QA-Pagelets from the Deep Web. ICDE 2004: 103-114 - [c1]James Caverlee, Ling Liu, Daniel Rocco:
Discovering and ranking web services with BASIL: a personalized approach with biased focus. ICSOC 2004: 153-162
Coauthor Index
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