Data

Tools

Indexes

Applications

Experiments

Awesome

An open API service indexing awesome lists of open source software.

https://github.com/renovamen/kg-application-papers

Paper list about application of Knowledge Graph | 知识图谱的应用相关论文
https://github.com/renovamen/kg-application-papers

Last synced: 3 months ago
JSON representation

Paper list about application of Knowledge Graph | 知识图谱的应用相关论文

Awesome Lists containing this project

README 

          
# A Survey on Application of Knowledge Graph



The papers mentioned in paper **A Survey on Application of Knowledge Graph**. All papers can be found in `\papers`.



[Better View](https://renovamen.ink/KG-Application-Papers/)



 



## Knowledge Bases



1. **DBpedia**



   **DBpedia-A crystallization point for the Web of Data.** *Christian Bizer, et al.* Web Semantics: Science, Services and Agents on the World Wide Web 2009. [[Paper]](https://www.sciencedirect.com/science/article/pii/S1570826809000225)



2. **YAGO**



   **Yago: A large ontology from wikipedia and wordnet.** *Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum.* Web Semantics: Science, Services and Agents on the World Wide Web 2008. [[Paper]](https://www.sciencedirect.com/science/article/pii/S1570826808000437)



3. **Wikidata** [[Website]](https://www.wikidata.org/wiki/Wikidata:Main_Page)



4. **Freebase**



   **Freebase: A shared database of structured general human knowledge.** *Kurt Bollacker, Robert Cook, and Patrick Tufts.* AAAI 2007. [[Paper]](https://www.aaai.org/Papers/AAAI/2007/AAAI07-355.pdf)



 



## Construction Techniques



1. **Knowledge graph construction techniques. (Chinese)** *Qiao Liu, Yang Li, Hong Duan, Yao Liu, Zhiguang Qing.* Journal of Computer Research and Development (计算机研究与发展) 2016. [[Paper]](http://crad.ict.ac.cn/CN/abstract/abstract3127.shtml#)



2. **Review on knowledge graph techniques.  (Chinese)** *Zenglin Xu, Yongpan Sheng, Lirong He, Yafang Wang.* Journal of University of Electronic Science and Technology of China (电子科技大学学报) 2016. [[Paper]](http://www.cnki.com.cn/Article/CJFDTotal-DKDX201604012.htm)



3. **Architecture of Knowledge Graph Construction Technique.** *Zhao, Zhanfang, Sung-Kook Han, and In-Mi So.* International Journal of Pure and Applied Mathematics 2018. [[Paper]](https://acadpubl.eu/jsi/2018-118-19/articles/19b/24.pdf)



 



## Application



### Question Answering System



#### Datasets



1. **WebQuestion**



   **Semantic parsing on freebase from question-answer pairs.** *Jonathan Berant, et al.* EMNLP 2013. [[Paper]](https://www.aclweb.org/anthology/D13-1160)



2. **SimpleQuestion**



   **Large-scale simple question answering with memory networks.** *Antoine Bordes, et al.* arXiv 2015. [[Paper]](https://arxiv.org/pdf/1506.02075.pdf)



#### Industry



1. **Building Watson: An overview of the DeepQA project.** *David Ferrucci, Eric Brown, Jennifer Chu-Carroll, et al.* AI Magazine 2010. [[Paper]](https://www.aaai.org/ojs/index.php/aimagazine/article/view/2303/2165)



2. **The Design and Implementation of XiaoIce, an Empathetic Social Chatbot.** *Li Zhou, Jianfeng Gao, Di Li, Heung-Yeung Shum.* arXiv 2018. [[Paper]](https://arxiv.org/pdf/1812.08989.pdf)



#### Semantic Parsing Based



1. **Semantic parsing on freebase from question-answer pairs.** *Jonathan Berant, Andrew Chou, Roy Frostig Percy Liang.* EMNLP 2013. [[Paper]](https://www.aclweb.org/anthology/D13-1160)

2.  **Open question answering over curated and extracted knowledge bases.** *Anthony Fader, Luke Zettlemoyer, and Oren Etzioni.* KDD 2014. [[Paper]](https://homes.cs.washington.edu/~lsz/papers/fze-kdd14.pdf) [[Code]](https://github.com/afader/oqa)



#### Information Retrievaling Based



1. **Information extraction over structured data: Question answering with freebase.** *Xuchen Yao, and Benjamin Van Durme.* ACl 2014. [[Paper]](http://cs.jhu.edu/~xuchen/paper/yao-jacana-freebase-acl2014.pdf)



#### Embedding Based



1. **Question answering with subgraph embeddings.** *Antoine Bordes, Sumit Chopra, and Jason Weston.* EMNLP 2014. [[Paper]](https://www.aclweb.org/anthology/D14-1067)



2.  **Joint relational embeddings for knowledge-based question answering.** *Min-Chul Yang, et al.* EMNLP 2014. [[Paper]](https://www.aclweb.org/anthology/D14-1071)

3. **Open question answering with weakly supervised embedding models.** *Antoine Bordes, Jason Weston, and Nicolas Usunier.* ECML PKDD 2014. [[Paper]](https://arxiv.org/pdf/1404.4326.pdf)



#### Deep Learning



1. **Question answering over freebase with multi-column convolutional neural networks.** *Li Dong, et al.* IJCNLP 2015. [[Paper]](https://www.aclweb.org/anthology/P15-1026)

2. **An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge.** *Yanchao Hao, et al.* ACL 2017. [[Paper]](https://www.aclweb.org/anthology/P17-1021)

3. **Semantic parsing via staged query graph generation: Question answering with knowledge base.** *Scott Wen-tau Yih, et al.* IJCNLP 2015. [[Paper]](https://www.aclweb.org/anthology/P15-1128)

4. **Question answering over knowledge base with neural attention combining global knowledge information.** *Yuanzhe Zhang, et al.* ACL 2016. [[Paper]](https://arxiv.org/pdf/1606.00979.pdf)

5. **A knowledge-grounded neural conversation model.** *Marjan Ghazvininejad, et al.* AAAI 2018. [[Paper]](https://www.microsoft.com/en-us/research/wp-content/uploads/2017/02/A_Knowledge_Grounded_Neural_Conversation_Model.pdf)



6. **Key-value memory networks for directly reading documents.** *Alexander Miller, et al.* ACL 2016. [[Paper]](https://aclweb.org/anthology/D16-1147)



#### More Complex QA Tasks



1. **Commonsense for Generative Multi-Hop Question Answering Tasks.** *Lisa Bauer, Yicheng Wang, and Mohit Bansal.* EMNLP 2018. [[Paper]](https://aclweb.org/anthology/D18-1454) [[Code]](https://github.com/yicheng-w/CommonSenseMultiHopQA)

2. **TEQUILA: Temporal Question Answering over Knowledge Bases.** *Zhen Jia, et al.* CIKM 2018. [[Paper]](http://qa.mpi-inf.mpg.de/tequila/p1807-jia.pdf)

3. **Generating factoid questions with recurrent neural networks: The 30m factoid question-answer corpus.** *Iulian Vlad Serban, et al.* ACL 2016. [[Paper]](https://www.aclweb.org/anthology/P16-1056)

4. **Transliteration Better than Translation? Answering Code-mixed Questions over a Knowledge Base.** *Vishal Gupta, Manoj Chinnakotla, and Manish Shrivastava.* CALCS 2018. [[Paper]](https://www.aclweb.org/anthology/W18-3205)

5. **KG^ 2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings.** *Yuyu Zhang, et al.* arXiv 2018. [[Paper]](https://arxiv.org/pdf/1805.12393.pdf)



 



### Recommender System



#### Embedding Based



1. **DKN: Deep knowledge-aware network for news recommendation.** *Hongwei Wang, et al.* WWW 2018. [[Paper]](https://arxiv.org/pdf/1801.08284.pdf)

2. **Collaborative knowledge base embedding for recommender systems.** *Fuzheng Zhang, et al.* KDD 2016. [[Paper]](https://www.kdd.org/kdd2016/papers/files/adf0066-zhangA.pdf)



3. **Shine: Signed heterogeneous information network embedding for sentiment link prediction.** *Hongwei Wang, et al.* WSDM 2018. [[Paper]](https://arxiv.org/pdf/1712.00732.pdf)



4. **Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation.** *Hongwei Wang, et al.* WWW 2019. [[Paper]](https://arxiv.org/pdf/1901.08907.pdf) [[Code]](https://github.com/hwwang55/MKR)



5. **Auto-encoding user ratings via knowledge graphs in recommendation scenarios.** *Vito Bellini, et al.* DLRS 2017. [[Paper]](https://arxiv.org/pdf/1706.07956.pdf)



#### Path Based



1. **Personalized entity recommendation: A heterogeneous information network approach.** *Xiao Yu, et al.* WSDM 2014. [[Paper]](http://hanj.cs.illinois.edu/pdf/wsdm14_xyu.pdf)



2. **Meta-graph based recommendation fusion over heterogeneous information networks.** *Huan Zhao, et al.* KDD 2017. [[Paper]](http://www.cse.ust.hk/~yqsong/papers/2017-KDD-HINRec-FMG.pdf)



3. **Explainable Reasoning over Knowledge Graphs for Recommendation.** *Xiang Wang, et al.* AAAI 2019. [[Paper]](https://arxiv.org/pdf/1811.04540.pdf) [[Code]](https://github.com/eBay/KPRN)



#### Others



1. **RippleNet: Propagating user preferences on the knowledge graph for recommender systems.** *Hongwei Wang, et al.* CIKM 2018. [[Paper]](https://arxiv.org/pdf/1803.03467.pdf) [[Code]](https://github.com/hwwang55/RippleNet)

2. **Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences.** WWW 2019. [[Paper]](https://arxiv.org/pdf/1902.06236.pdf)



 



### Information Retrieval



1. **Entity query feature expansion using knowledge base links.** *Jeffrey Dalton, Laura Dietz, and James Allan.* SIGIR 2014. [[Paper]](https://ciir-publications.cs.umass.edu/pub/web/getpdf.php?id=1143)



2. **Latent entity space: a novel retrieval approach for entity-bearing queries.** *Xitong Liu, and Hui Fang.* Information Retrieval Journal 2015. [[Paper]](https://link.springer.com/article/10.1007/s10791-015-9267-x)



3. **Esdrank: Connecting query and documents through external semi-structured data.** *Chenyan Xiong, and Jamie Callan.* CIKM 2015. [[Paper]](https://www.cs.cmu.edu/~callan/Papers/cikm15-cx.pdf)



4. **Word-entity duet representations for document ranking.** *Chenyan Xiong, Jamie Callan, and Tie-Yan Liu.* SIGIR 2017. [[Paper]](https://arxiv.org/pdf/1706.06636.pdf)



5. **Bag-of-Entities representation for ranking.** *Chenyan Xiong, Jamie Callan, and Tie-Yan Liu.* ICTIR 2016. [[Paper]](http://www.cs.cmu.edu/~cx/papers/Bag_of_Entities_Representation_for_Ranking.pdf)



6. **Document retrieval using entity-based language models.** *Hadas Raviv, Oren Kurland, and David Carmel.* SIGIR 2016. [[Paper]](https://iew3.technion.ac.il/~kurland/p65-raviv.pdf)



7. **Document retrieval model through semantic linking.** *Faezeh Ensan, and Ebrahim Bagheri.* WSDM 2017. [[Paper]](https://dl.acm.org/citation.cfm?id=3018692)



8. **Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval.** *Zhenghao Liu, et al.* ACL 2018. [[Paper]](https://aclweb.org/anthology/P18-1223) [[Code]](https://github.com/thunlp/EntityDuetNeuralRanking)

9. **Explicit semantic ranking for academic search via knowledge graph embedding.** *Chenyan Xiong, Russell Power, and Jamie Callan.* WWW 2017. [[Paper]](https://ai2-website.s3.amazonaws.com/publications/Explicit_Semantic_Ranking.pdf)



 



### Domain-Specific



#### Biomedical



1. **Knowlife: a knowledge graph for health and life sciences.** *Patrick Ernst, et al.* ICDE 2014. [[Paper]](https://ieeexplore.ieee.org/document/6816754)

2. **Semantic health knowledge graph: Semantic integration of heterogeneous medical knowledge and services.** *Longxiang Shi, et al.* BioMed research international 2017. [[Paper]](https://www.hindawi.com/journals/bmri/2017/2858423/)

3. **Automatic generation of a qualified medical knowledge graph and its usage for retrieving patient cohorts from electronic medical records.** *Travis Goodwin, and Sanda M. Harabagiu.* ICSC 2013. [[Paper]](https://www.hindawi.com/journals/bmri/2017/2858423/)

4. **Learning a health knowledge graph from electronic medical records.** *Maya Rotmensch, et al.* Scientific Reports 2017. [[Paper]](https://www.nature.com/articles/s41598-017-05778-z)



#### Cyber Security



1. **A Practical Approach to Constructing a Knowledge Graph for Cybersecurity.** *Yan Jia, et al.* Engineering 2018. [[Paper]](https://www.sciencedirect.com/science/article/pii/S2095809918301097)

2. **Developing an Ontology for Cyber Security Knowledge Graphs.** *Michael D Iannacone, et al.* CISR 2015. [[Paper]](https://dl.acm.org/citation.cfm?doid=2746266.2746278)

3. **Association Analysis Algorithm Based on Knowledge Graph for SPACE-Ground Integrated Network.** *Yulu Qi, et al.* ICCT 2018. [[Paper]](https://ieeexplore.ieee.org/abstract/document/8600234)

4. **ISEK: An information security knowledge graph for CISP knowledge system.** *Yuangang Yao, et al.* ICITCS 2015. [[Paper]](https://ieeexplore.ieee.org/abstract/document/7292991)

5. **Powering filtration process of cyber security ecosystem using knowledge graph.** *Claude Asamoah, et al.* CSCloud 2016. [[Paper]](https://ieeexplore.ieee.org/abstract/document/7545925/)



#### Financial



1. **Combining Enterprise Knowledge Graph and News Sentiment Analysis for Stock Price Volatility Prediction.** *Jue Liu, Zhuocheng Lu, and Wei Du.* HICSS 2019. [[Paper]](https://scholarspace.manoa.hawaii.edu/bitstream/10125/59565/0125.pdf)

2. **Cyber incident classifications using ontology-based knowledge representation for cybersecurity insurance in financial industry.** *Sam Adam Elnagdy, Meikang Qiu, and Keke Gai.* CSCloud 2016. [[Paper]](https://ieeexplore.ieee.org/abstract/document/7545936/)

3. **Understanding taxonomy of cyber risks for cybersecurity insurance of financial industry in cloud computing.** *Sam Adam Elnagdy, Meikang Qiu, and Keke Gai.* CSCloud 2016. [[Paper]](https://ieeexplore.ieee.org/abstract/document/7545935/)

4. **Constructing Knowledge Graphs with Trust.** *Brian Ulicny.* METHOD 2015. [[Paper]](https://www.researchgate.net/profile/Brian_Ulicny/publication/283500696_Constructing_Knowledge_Graphs_with_Trust/links/563b657308ae45b5d2867e2e.pdf)



#### News



1. **DKN: Deep knowledge-aware network for news recommendation.** *Hongwei Wang, et al.* WWW 2018. [[Paper]](https://arxiv.org/pdf/1801.08284.pdf)

2. **Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata.** *Charlotte Rudnik, et al.* Wiki Workshop 2019. [[Paper]](https://arxiv.org/pdf/1904.05557.pdf)

3. **Fact checking in heterogeneous information networks.** *Baoxu Shi, and Tim Weninger.* WWW 2016. [[Paper]](https://pdfs.semanticscholar.org/0ec3/89be2af8febd9612cc852e6894c930f299c5.pdf)

4. **Building event-centric knowledge graphs from news.** *Marco Rospocher, et al.* Journal of Web Semantics 2016. [[Paper]](https://www.sciencedirect.com/science/article/pii/S1570826815001456)

5. **Computational fact checking from knowledge networks.** *Giovanni Luca Ciampaglia, et al.* PLoS ONE 2015. [[Paper]](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128193)

6. **Fake News Detection on Social Media: A Data Mining Perspective.** *Kai Shu, et al.* SIGKDD 2017. [[Paper]](https://www.kdd.org/exploration_files/19-1-Article2.pdf)



#### Geoscience



1. **Information extraction and knowledge graph construction from geoscience literature.** *Chengbin Wang, et al.* Computers & Geosciences 2018. [[Paper]](https://www.sciencedirect.com/science/article/pii/S0098300417309020)



2. **Intelligent learning for knowledge graph towards geological data.** *Yueqin Zhu, et al.* Scientific Programming 2017. [[Paper]](https://www.hindawi.com/journals/sp/2017/5072427/)



#### Education



1. **KnowEdu: A System to Construct Knowledge Graph for Education.** *Penghe Chen, et al.* IEEE Access 2018. [[Paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8362657&tag=1)

2. **Knowledge graph-based teacher support for learning material authoring.** *Christian Grévisse, et al.* CCC 2018. [[Paper]](https://link.springer.com/chapter/10.1007/978-3-319-98998-3_14)

3. **Visualization for Knowledge Graph Based on Education Data.** *Kai Sun, et al.* IJSI 2016. [[Paper]](http://ijsi.alljournals.cn/ch/reader/create_pdf.aspx?file_no=i227&flag=1&journal_id=ijsi&year_id=2016)



 



### Other Applications



#### Social Network



1. **Social network de-anonymization and privacy inference with knowledge graph model.** *Jianwei Qian, et al.* IEEE TDSC 2017. [[Paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7911249)

2. **De-anonymizing Social Networks and Inferring Private Attributes Using Knowledge Graphs.** *Jianwei Qian, et al.*  IEEE INFOCOM 2016. [[Paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7524578)



#### Classification



1. **Sentiment Analysis**



   **Targeted aspect-based sentiment analysis via embedding commonsense knowledge into an attentive LSTM.** *Yukun Ma, Haiyun Peng, and Erik Cambria.* AAAI 2018. [[Paper]](https://sentic.net/sentic-lstm.pdf)



2. **Image Classification**



   **Knowledge Graph-Based Image Classification Refinement.** *Dehai Zhang, et al.* IEEE Access 2019. [[Paper]](https://ieeexplore.ieee.org/abstract/document/8698455)



3. **Text Classification**  



   **Combining Knowledge with Deep Convolutional Neural Networks for Short Text Classification.** *Jin Wang, et al.* IJCAI 2017. [[Paper]](https://www.ijcai.org/proceedings/2017/0406.pdf)



#### Word Embedding



- **RC-NET: A General Framework for Incorporating Knowledge into Word Representations.** *Chang Xu, et al.* CIKM 2014. [[Paper]](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/5BCIKM20145D20RC-NET.pdf)



#### Combating Human Trafficking



- **Building and using a knowledge graph to combat human trafficking.** *Pedro Szekely, et al.* ISWC 2015. [[Paper]](https://usc-isi-i2.github.io/papers/szekely15-iswc.pdf)