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https://github.com/suamin/awesome-kg-qaie

Awesome quickstart readings and resources for KGs with applications in QA and IE.
https://github.com/suamin/awesome-kg-qaie

List: awesome-kg-qaie

awesome awesome-list information-extraction knowledge-base knowledge-graph question-answering

Last synced: 16 days ago
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Awesome quickstart readings and resources for KGs with applications in QA and IE.

Host: GitHub
URL: https://github.com/suamin/awesome-kg-qaie
Owner: suamin
Created: 2021-03-16T13:38:16.000Z (almost 4 years ago)
Default Branch: main
Last Pushed: 2022-04-08T14:39:23.000Z (over 2 years ago)
Last Synced: 2024-05-23T04:14:08.653Z (7 months ago)
Topics: awesome, awesome-list, information-extraction, knowledge-base, knowledge-graph, question-answering
Homepage:
Size: 9.77 KB
Stars: 6
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

ultimate-awesome - awesome-kg-qaie - Awesome quickstart readings and resources for KGs with applications in QA and IE. (Other Lists / Monkey C Lists)

README

        # Awesome - KGs in QA and IE

[![MIT License](https://img.shields.io/badge/license-MIT-green.svg)](https://opensource.org/licenses/MIT) [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

A curated list of awesome surveys, books, theses and scholars working on Knowledge Graphs with focus on applications for Question Answering and Information Extraction.

# Knowledge Graphs: Representation, Reasoning and Applications

- Knowledge Graph Embedding: A Survey of Approaches and Applications [[Wang et al., 2017]](https://persagen.com/files/misc/Wang2017Knowledge.pdf)

- A review: Knowledge reasoning over knowledge graph [[Chen et al., 2020]](https://www.sciencedirect.com/science/article/abs/pii/S0957417419306669)

- A survey of embedding models of entities and relationships for knowledge graph completion [[Nguyen et al., 2020]](https://www.aclweb.org/anthology/2020.textgraphs-1.1.pdf)

- A Survey on Knowledge Graph Embedding: Approaches, Applications and Benchmarks [[Dai et al., 2020]](https://www.mdpi.com/2079-9292/9/5/750/htm)

- A Survey on Graph Neural Networks for Knowledge Graph Completion [[Arora et al., 2020]](https://arxiv.org/pdf/2007.12374.pdf)

- A Survey on Knowledge Graphs - Representation, Acquisition and Applications [[Ji et al., 2021]](https://arxiv.org/pdf/2002.00388.pdf)

- Knowledge Graph Embedding for Link Prediction: A Comparative Analysis [[Rossi et al., 2021]](https://arxiv.org/pdf/2002.00819.pdf)

- Neural-Symbolic Reasoning on Knowledge Graphs [[Zhang et al., 2020]](https://arxiv.org/pdf/2010.05446.pdf)

- Combining pre-trained language models and structured knowledge [[Colon-Hernandez et al., 2021]](https://arxiv.org/pdf/2101.12294.pdf)

# ML/DL with Graphs

- Representation Learning on Graphs - Methods and Applications [[Hamilton et al., 2018]](https://arxiv.org/pdf/1709.05584.pdf)

- A Comprehensive Survey on Graph Neural Networks [[Wu et al., 2020]](https://arxiv.org/pdf/1901.00596.pdf)

- Deep Learning on Graphs: A Survey [[Zhang et al., 2020]](https://arxiv.org/pdf/1812.04202.pdf)

- Machine Learning on Graphs: A Model and Comprehensive Taxonomy [[Chami et al., 2021]](https://arxiv.org/pdf/2005.03675.pdf)

# Question Answering

- Introduction to neural network-based question answering over knowledge graphs [[Chakraborty et al., 2020]](https://onlinelibrary.wiley.com/doi/epdf/10.1002/widm.1389)

- An Overview of Utilizing Knowledge Bases in Neural Networks for Question [[Kafle et al., 2019]](https://par.nsf.gov/servlets/purl/10131233)

- A Survey on Complex Question Answering over Knowledge Base - Recent Advances and Challenges [[Fu et al., 2020]](https://arxiv.org/pdf/2007.13069.pdf)

- Recent Trends in Deep Learning Based Open-Domain Textual Question Answering Systems [[Huang et al., 2020]](https://ieeexplore.ieee.org/iel7/6287639/8948470/09072442.pdf)

# Information Extraction

- A Survey on Open Information Extraction [[Niklaus et al., 2018]](https://www.aclweb.org/anthology/C18-1326.pdf)

- A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs [[Sun et al., 2020]](https://arxiv.org/pdf/2003.07743.pdf)

- Neural relation extraction: a survey [[Aydar et al., 2020]](https://arxiv.org/pdf/2007.04247.pdf)

- Techniques for Jointly Extracting Entities and Relations: A Survey [[Pawar et al., 2021]](https://arxiv.org/pdf/2103.06118.pdf)

# Books

- Machine Knowledge - Creation and Curation of Comprehensive Knowledge Bases [[Weikum et al., 2020]](https://arxiv.org/pdf/2009.11564.pdf)

- Graph Representation Learning [[Hamilton, 2020]](https://www.cs.mcgill.ca/~wlh/grl_book/files/GRL_Book.pdf)

# PhD Theses

- Tensor Factorization for Relational Learning [[Maximilian Nickel, 2013]](https://edoc.ub.uni-muenchen.de/16056/1/Nickel_Maximilian.pdf)

- Complex-Valued Embedding Models for Knowledge Graphs [[Theo Trouillon, 2017]](https://tel.archives-ouvertes.fr/tel-01692327/file/TROUILLON_2017_archivage.pdf)

- Representing and Learning Relations and Properties Under Uncertainty [[Seyed Mehran Kazemi, 2018]](https://open.library.ubc.ca/cIRcle/collections/ubctheses/24/items/1.0375812)

- Large-Scale Machine Learning over Graphs [[Hanxiao Liu, 2018]](https://lti.cs.cmu.edu/sites/default/files/liu%2C%20hanxiao.pdf)

- Multi-relational Representation Learning and Knowledge Acquisition [[Muhao Chen, 2019]](https://escholarship.org/content/qt373677v6/qt373677v6.pdf?t=ps9h6f)

- Reasoning-Driven Question-Answering for Natural Language Understanding [[Daniel Khashabi, 2019]](https://arxiv.org/pdf/1908.04926.pdf)

- Tensor Decompositions for Knowledge Base Completion [[Timothee Lacroix, 2020]](https://www.theses.fr/2020PESC1002.pdf)

- Using Knowledge Bases for Question Answering [[Yunshai Lan, 2020]](https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1261&context=etd_coll)

- End-to-End Learning with Text & Knowledge Bases [[Bhuwan Dhingra, 2020]](https://www.cs.cmu.edu/~bdhingra/docs/bhuwan_dhingra_thesis.pdf)

- Neural Interface for Web-Scale Knowledge [[Minjoon Seo, 2020]](https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/45926/Seo_washington_0250E_21539.pdf?sequence=1&isAllowed=y)

- Representation Learning for Graph-Structured Data [[Dai Quoc Nguyen, 2021]](https://au-east.erc.monash.edu.au/fpfiles/27643737/DAI_PHD_THESIS_Final.pdf)

- Learning representations of entities and relations [[Ivana Balažević, 2021]](https://arxiv.org/ftp/arxiv/papers/2201/2201.13073.pdf)

# Scholars

- [Jing Jiang](https://scholar.google.com/citations?user=hVTK2YwAAAAJ&hl=en)

- [Partha Pratim Talukdar](https://scholar.google.com/citations?user=CIZwXAcAAAAJ&hl=en)

- [Rainer Gemulla](https://scholar.google.de/citations?user=s_GmFv0AAAAJ&hl=de)

- [Sebastian Riedel](https://scholar.google.com/citations?user=AcCtcrsAAAAJ&hl=en)

- [Shirui Pan](https://scholar.google.com.au/citations?user=frWRJN4AAAAJ&hl=en)

- [William L. Hamilton](https://scholar.google.com/citations?user=T5tm9eQAAAAJ&hl=en)

- [William W. Cohen](https://scholar.google.com/citations?user=8ys-38kAAAAJ&hl=en)

- [Zhiyuan Liu](https://scholar.google.com/citations?user=dT0v5u0AAAAJ&hl=en)

# Frameworks

- [OpenKE](https://github.com/thunlp/OpenKE)

- [kge](https://github.com/uma-pi1/kge)

- [PyKEEN](https://github.com/pykeen/pykeen)

- [dgl-ke](https://github.com/awslabs/dgl-ke)

- [AmpliGraph](https://github.com/Accenture/AmpliGraph)

- [KILT](https://github.com/facebookresearch/KILT)

- [BLINK](https://github.com/facebookresearch/BLINK)

# Courses

- [CS224W: Machine Learning with Graphs](https://web.stanford.edu/class/cs224w/)

- [COMP 766 - Graph Representation Learning](https://cs.mcgill.ca/~wlh/comp766/index.html)

- [MPI - Advanced Topics in Knowledge Bases](https://www.mpi-inf.mpg.de/departments/databases-and-information-systems/teaching/ws1819/advanced-topics-in-knowledge-bases)

- [CS953 Adv Top - Data Science for Knowledge Graphs and Text](https://www.cs.unh.edu/~dietz/teaching/ds/index.html)

# Collections

Related collections:

- [KGE](https://github.com/xinguoxia/KGE)

- [KRLPapers](https://github.com/thunlp/KRLPapers)

- [KGEPapers](https://github.com/MIRALab-USTC/KGEPapers)

- [KGRPapers](https://github.com/MIRALab-USTC/KGRPapers)

- [awesome-qa](https://github.com/seriousran/awesome-qa)

- [InformationExtraction](https://github.com/casnlu/InformationExtraction)

- [GNNPapers](https://github.com/thunlp/GNNPapers)

- [graph-based-deep-learning-literature](https://github.com/naganandy/graph-based-deep-learning-literature)