Notes: Personally, these are the papers that have a very clear presentation to formulate and solve a problem / to construct a system.
Papers that define problems
- The Community-search Problem and How to Plan a Successful Cocktail Party (KDD 2010) [Paper]
- Optimizing DNN Computation Graph using Graph Substitutions (VLDB 2020)
- Robust Discovery of Positive and Negative Rules in Knowledge Bases (ICDE 2018) [Paper]
- Interpretable Decision Sets: A Joint Framework for Description and Prediction (KDD 2016) [Paper]
- LSH Ensemble: Internet-Scale Domain Search [Paper] [GitHub]
- Property Graph Schema Optimization for Domain-Specific Knowledge Graphs (ICDE 2021) [Paper]
- Scaling Atributed Network Embedding to Massive Graphs (VLDB 2021 Best paper!) [Paper] [Datasets] [Slides]
Papers that build systems
- NeuGraph: Parallel Deep Neural Network Computation on Large Graphs (USENIX 2019) [Paper]
- Optimizing Machine Learning Workloads in Collaborative Environments (SIGMOD 2020) [Paper]
Some Graph things
- On the Minimum Common Supergraph of Two Graphs
- Graph Indexing: A Frequent Structure-based Approach (SIGMOD 2004) [Paper]
- Clique Relaxation Models in Networks: Theory, Algorithms, and Applications [Slides]
- Parallel Local Graph Clustering [Paper]
Graph Matching
- The graph matching problem [Link]
- Subgraph Matching Kernels for Attributed Graphs [Paper]
- Graph Similarity Search with Edit Distance Constraint in Large Graph Databases [Paper]
Good Writing
- LASAGNE: Locality And Structure Aware Graph Node Embedding [Paper]
Others
- NP Optimization Problems [Link]
- Greedy Set-Cover Algorithms [Paper]