Note: The papers in database area (or written in database style) are marked with 🌟

• Knowledge Base Construction (Demo or System) [link]

• About Domain-Specific Knowledge Bases [link]

• Named Entity Recoginition, Entity Extraction and Entity Typing [link]

• Coreference Resolution [link]

• Entity Linking and Entity Disambiguation [link]

• Entity Resolution, Entity Matching and Entity Alignment [link]

• General Relation Extraction [link]

• Open Information Extraction [link]

• Relation Linking and Relation Disambiguation [link]

• Knowledge Graph Embedding, Learning, Reasoning, Rule Mining, and Path Finding [link]

• Knowledge Base Refinement (Incompleteness, Incorrectness, and Freshness) [link]

• Knowledge Fusion, Cleaning, Evaluation and Truth Discovery [link]

• Knowledge Graph Question Answering (KGQA) [link]

• Knowledge Graph Recommendation [link]

• Other Interesting Works [link]

• Good DB Papers [link]

1. An introduction to knowledge graph and knowledge extraction from unstructured text. [Link]
2. Information Extraction by Niranjan Balasubramanian {Slides in my Mac}
3. CS 520 - Knowledge Graphs (seminar) - provided by Stanford
4. OpenKG.cn

1. A Collection of KG Surveys, Papers (WWW+ACL+AAAI) and Data [GitHub]
2. KG STOA [GitHub]
3. Awesome KG tutorials/papers/projects/communities [GitHub]
4. Knowledge Graph Construction (from zero to everything, in Chinese) [GitHub]
5. KG STOA (Chinese) [Zhihu]
6. Tracking Progress in Natural Language Processing [GitHub]
7. KG Embedding STOA [GitHub]

1. Probabilistic Graphical Models: Lagrangian Relaxation Algorithms for Natural Language Processing [Slides]
2. Introduction to Conditional Random Fields [Blog]
3. Network Community Detection: A Review and Visual Survey [Paper]

• Section 2.3. Community Detection Techniques

4. Fast unfolding of communities in large networks [Paper]

• [A discussion of the Louvain method], [wiki of the Louvein Modularity]
• How do they design the function Q: Finding and evaluating community structure in networks [Paper]

5. A compendium of NP optimization problems [Paper]
6. [Notes about LSH]
7. [Survey about Min Hash Sketch]
8. MinHash Tutorial with Python Code: [Notes] [Code]
9. Must-read papers on GNN [GitHub]
10. Graph-based deap learning literatures [GitHub]
11. Data Management for Machine Learning Applications [Course site]

1. TagMe [Python API] [API] [GitHub1] [GitHub2]
2. Stanford NER [Link]
3. DBpeida Spotlight [Link]
4. NLTK Tagger [Link]
5. SpaCy [Link1] [Link2]
6. EARL (including Relation Linking) [Link]
7. Falcon (including Relatoin Linking) [DBpedia version] [Wikidata version]
8. MonkeyLearn [Link]
9. GERBIL - General Entity Annotator Benchmark [Link]

1. Entity Disambiguation:

• MSNBC and ACE2004 [Link]

2. QA:

• WebQuestions
• QA datasets summary [GitHub]

3. Entity Resolution [GitHub]

1. From Freebase to Wikidata: The Great Migration [Paper and useful links]
2. SPASQL tutorial [Link]
3. Installing and running ElasticSearch [Link]
4. Open KG on COVID-19 [Link]
5. BOOKNLP [Link] (Pronominal Coreference Resolution, a natural language processing pipeline that scales to books and other long documents (in English))
6. Wikidata Integrator [GitHub]
7. OpenTapioca [Link]