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- Scope learning (1 revision - redirect page)
- Review for Exploiting Relational Structure to Understand Publication Patterns in High-Energy Physics (1 revision)
- Textual topics and network are combined (1 revision)
- ArXiv Comprehensive (1 revision)
- Flick dataset (1 revision)
- Result (1 revision)
- Coreference Resolution in a Modular, Entity-Centered Model (1 revision)
- Graph Generation (1 revision)
- Twitter (1 revision)
- ACL Antology (1 revision)
- This paper demonstrates how each of these methods can divide the structure of large-scale network. (1 revision)
- Technorati Dataset (1 revision)
- Jensen-Shannon divergence (1 revision)
- Forest Fire (1 revision)
- Explain the downward movement of stock prices using sentiment analysis methods (1 revision)
- Identify the latent class as well as dyadic events (1 revision)
- Convex programming (1 revision)
- Hu SIGKDD 2004 (1 revision)
- Project Project Second Draft Proposal:Daniel and Sherry (1 revision - redirect page)
- SlashDot dataset (1 revision)
- Co-occurrence agreement probability (1 revision)
- Viterbi (1 revision)
- LiveJournal post stream gathered using atom listener (1 revision)
- Social Network Attribute (1 revision - redirect page)
- Project Adam Gabriel (1 revision - redirect page)
- Markov chain (1 revision)
- 28 subjects (1 revision)
- Language evolution (1 revision)
- Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks. Workshop on Statistical Network Analysis, held at the 23 rd International Conference on Machine Learning, 2006. (1 revision)
- Hierarchical Dirichlet process (1 revision)
- TREC BLOG06 (1 revision)
- Vladimir Ouzienko, Prediction of Attributes and Links in Temporal Social Networks. (1 revision)
- Cora (1 revision)
- Graphical Games (1 revision)
- Privacy attacks (1 revision)
- NIPS 1988-1999 (1 revision)
- Social problem-solving (1 revision)
- Linear Threshold Models - Diffusion models (1 revision)
- CiteSeer (1 revision)
- Kearns NAS 2006 (1 revision)
- CRF (1 revision - redirect page)
- Proposed a discrete temporal model family that is capable of modeling network evolution, while maintaining the flexibility of ERGMs. It also proposed such models to build upon ERGMs as much as possible. (1 revision)
- Normalized Learning (1 revision)
- Identifying high-quality content in social media sites (1 revision)
- Hill Climbing (1 revision)
- Simulating Ordinal Time from Snapshots (1 revision)
- Feedback effects between similarity and social influence in online communities (1 revision)
- Several methods are used in this paper (1 revision)
- Question-Answer Sharing Analysis (1 revision)
- Machine Learning with Large Datasets - course proposal (1 revision - redirect page)
