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https://github.com/mickeysjm/awesome-taxonomy
A curated resource for taxonomy research
https://github.com/mickeysjm/awesome-taxonomy
List: awesome-taxonomy
datasets hypernymy-detection taxonomy-construction taxonomy-learning
Last synced: 16 days ago
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A curated resource for taxonomy research
- Host: GitHub
- URL: https://github.com/mickeysjm/awesome-taxonomy
- Owner: mickeysjm
- Created: 2019-02-07T05:04:26.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2024-04-26T23:34:12.000Z (8 months ago)
- Last Synced: 2024-05-20T06:12:03.529Z (7 months ago)
- Topics: datasets, hypernymy-detection, taxonomy-construction, taxonomy-learning
- Size: 83 KB
- Stars: 198
- Watchers: 20
- Forks: 30
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# awesome-taxonomy
A curated resource for taxonomy research# Datasets / Shared Tasks
1. SemEval-2015 Task 17: Taxonomy Extraction Evaluation (TExEval-1), [Home](http://alt.qcri.org/semeval2015/task17/), [Report](http://aclweb.org/anthology/S15-2151)
2. SemEval-2016 Task 13: Taxonomy Extraction Evaluation (TExEval-2), [Home](http://alt.qcri.org/semeval2016/task13/), [Report](http://www.aclweb.org/anthology/S16-1168)
3. SemEval-2016 Task 14: Semantic Taxonomy Enrichment, [Home](http://alt.qcri.org/semeval2016/task14/), [Report](https://www.aclweb.org/anthology/S16-1169)
4. SemEval-2018 Task 9: Hypernym Discovery, [Home](https://competitions.codalab.org/competitions/17119), [Report](http://aclweb.org/anthology/S18-1115)
5. UnsupervisedHypernymy, [Home](https://github.com/vered1986/UnsupervisedHypernymy), [EACL 2017 paper](https://www.aclweb.org/anthology/E17-1007), including 4 datasets:
* (Hypernymy Detection): EVAL, BLESS, LEDS (a.k.a Lenci/Benotto), Weeds
6. HypernymySuite, [Home](https://github.com/facebookresearch/hypernymysuite), [ACL 2018 paper](https://www.aclweb.org/anthology/P18-2057), including (somewhat modified) datasets:
* (Hypernymy Detection): BLESS, LEDS, EVAL, SHWARTZ, WBLESS
* (Hypernymy Direction): BLESS, WBLESS, BIBLESS
* (Graded Entailment): HyperLex# Paper
## Book & Survey & Tutorials
- \[ACL 2017\] [A Short Survey on Taxonomy Learning from Text Corpora: Issues, Resources and Recent Advances](http://aclweb.org/anthology/D17-1123)
- \[ICDM 2021\] [Automated Taxonomy Discovery and Exploration](https://mickeysjm.github.io/resources/icdm21_tutorial.pdf)
* Slides: [https://drive.google.com/drive/folders/1e_wb0MWydNPSEtZGD6g8ZLM-5Q_OtQdh](https://drive.google.com/drive/folders/1e_wb0MWydNPSEtZGD6g8ZLM-5Q_OtQdh)- \[Springer Nature 2022\] [Automated Taxonomy Discovery and Exploration](https://link.springer.com/book/10.1007/978-3-031-11405-2)
## Hypernymy Discovery & Lexical Entailment
- \[IJCAI 2015\] [Learning Term Embeddings for Hypernymy Identification](https://www.ijcai.org/Proceedings/15/Papers/200.pdf)
- \[ACL 2016\] [Improving Hypernymy Detection with an Integrated Path-based and Distributional Method](https://www.aclweb.org/anthology/P16-1226) (HypeNet)
* Code: [https://github.com/vered1986/HypeNET](https://github.com/vered1986/HypeNET)
- \[COLING 2016 CogALex-V\] [LexNET -- Integrated Path-based and Distributional Method for the Identification of Semantic Relations](https://www.aclweb.org/anthology/W16-5310)
* Code: [https://github.com/vered1986/LexNET](https://github.com/vered1986/LexNET)
- \[SemEval 2016\] [TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling](https://www.aclweb.org/anthology/S16-1206)
- \[EMNLP 2016\] [Relations such as Hypernymy: Identifying and Exploiting Hearst Patterns in Distributional Vectors for Lexical Entailment](https://aclweb.org/anthology/D16-1234)
* Code: [https://github.com/stephenroller/emnlp2016](https://github.com/stephenroller/emnlp2016)
- \[EMNLP 2016\] [Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network](https://www.aclweb.org/anthology/D16-1039)
- \[EACL 2017\] [Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection](https://www.aclweb.org/anthology/E17-1007)
* Code: [https://github.com/vered1986/UnsupervisedHypernymy](https://github.com/vered1986/UnsupervisedHypernymy)
- \[EMNLP 2017\] [Hierarchical Embeddings for Hypernymy Detection and Directionality](https://aclweb.org/anthology/papers/D/D17/D17-1022/) (HyperVec)
* Code: [https://github.com/nguyenkh/HyperVec](https://github.com/nguyenkh/HyperVec)
- \[NAACL 2018\] [Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection](https://www.aclweb.org/anthology/N18-1045)
- \[NAACL 2018\] [Specialising Word Vectors for Lexical Entailment](https://www.aclweb.org/anthology/N18-1103)
* Code: [https://github.com/nmrksic/lear](https://github.com/nmrksic/lear)
- \[SEM 2018\] [Term Definitions Help Hypernymy Detection](https://www.aclweb.org/anthology/S18-2025)
- [Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora](https://www.aclweb.org/anthology/P18-2057) \[ACL 2018\]
* Code: [https://github.com/facebookresearch/hypernymysuite](https://github.com/facebookresearch/hypernymysuite)
- \[AAAI 2019\] [Improving Hypernymy Prediction via Taxonomy Enhanced Adversarial Learning](https://chywang.github.io/papers/aaai2019.pdf)
* Code: [https://github.com/chywang/TEAL](https://github.com/chywang/TEAL)
- \[WWW 2019\] [A Family of Fuzzy Orthogonal Projection Models for Monolingual and Cross-lingual Hypernymy Prediction](https://chywang.github.io/papers/www2019.pdf)
* Code: [https://github.com/chywang/FOP](https://github.com/chywang/FOP)
- \[CIKM 2019\] [Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity](https://arxiv.org/pdf/1909.01584.pdf)
* Code: [https://github.com/ysyushi/HyperMine](https://github.com/ysyushi/HyperMine)
- \[AAAI 2020\] [Hypernym Detection Using Strict Partial Order Networks](https://arxiv.org/pdf/1909.10572.pdf)
- \[ACL 2020\] [BiRRE: Learning Bidirectional Residual Relation Embeddings for Supervised Hypernymy Detection](https://chywang.github.io/papers/acl2020.pdf)
- \[ACL 2020\] [Hypernymy Detection for Low-Resource Languages via Meta Learning](https://www.aclweb.org/anthology/2020.acl-main.336.pdf)
- \[EMNLP 2020\] [When Hearst Is not Enough: Improving Hypernymy Detection from Corpus with Distributional Models](https://arxiv.org/pdf/2010.04941.pdf)
* Code: [https://github.com/HKUST-KnowComp/ComHyper](https://github.com/HKUST-KnowComp/ComHyper)
- \[ACL 2021 Findings\] [Hypernym Discovery via a Recurrent Mapping Model](https://aclanthology.org/2021.findings-acl.257.pdf)
- \[ACL 2021 Findings\] [More than just Frequency? Demasking Unsupervised Hypernymy Prediction Method](https://arxiv.org/pdf/2106.00055.pdf)
* Code: [https://github.com/Thommy96/hyp-freq-comp](https://github.com/Thommy96/hyp-freq-comp)
- \[\*SEM 2023\] [Seeking Clozure: Robust Hypernym Extraction from BERT with Anchored Prompts](https://aclanthology.org/2023.starsem-1.18.pdf)
* Code: [https://github.com/ChunhuaLiu596/AnchoredPrompts](https://github.com/ChunhuaLiu596/AnchoredPrompts)
- \[EMNLP 2023\] [KEPL: Knowledge Enhanced Prompt Learning for Chinese Hypernym-Hyponym Extraction](https://aclanthology.org/2023.emnlp-main.358.pdf)## Concept Taxonomy Construction (Instance-based Taxonomy)
- \[ACL 2006\] [Semantic Taxonomy Induction from Heterogenous Evidence](http://aclweb.org/anthology/P06-1101)
- \[AAAI 2007\] [Deriving a Large Scale Taxonomy from Wikipedia](https://pdfs.semanticscholar.org/c360/b473ae80b715c5b725c592b6ab04fd4ac430.pdf)
- \[ACL 2009\] [A Metric-based Framework for Automatic Taxonomy Induction](http://aclweb.org/anthology/P09-1031)
- \[EMNLP 2010\] [A Semi-Supervised Method to Learn and Construct Taxonomies using the Web](http://aclweb.org/anthology/D10-1108)
- \[CIKM 2010\] [MENTA: Inducing Multilingual Taxonomies from Wikipedia](http://gerard.demelo.org/papers/demelo-menta-cikm2010.pdf)
- \[IJCAI 2011\] [A graph-based algorithm for inducing lexical taxonomies from scratch](https://www.ijcai.org/Proceedings/11/Papers/313.pdf)
- \[SIGMOD 2012\] [Probase: A probabilistic taxonomy for text understanding](https://www.microsoft.com/en-us/research/wp-content/uploads/2012/05/paper.pdf)
- \[ACL 2014\][Learning Semantic Hierarchies via Word Embeddings](https://www.aclweb.org/anthology/P14-1113)
- \[ACL 2014\] [Two Is Bigger (and Better) Than One -- the Wikipedia Bitaxonomy Project](http://aclweb.org/anthology/P14-1089)
* Resources: [http://wibitaxonomy.org/](http://wibitaxonomy.org/)
- \[ACL 2014\] [Structured Learning for Taxonomy Induction with Belief Propagation](http://aclweb.org/anthology/P14-1098)
- \[EMNLP 2014\] [Taxonomy Construction Using Syntactic Contextual Evidence](http://aclweb.org/anthology/D14-1088)
- \[EMNLP 2015\] [Incorporating Trustiness and Collective Synonym and Contrastive Evidence into Taxonomy Construction](http://aclweb.org/anthology/D15-1117)
- \[ICDM 2015\] [Automatic Taxonomy Extraction from Bipartite Graphs](https://ieeexplore.ieee.org/document/7373326)
- \[ACL 2016\] [Learning Concept Taxonomies from Multi-modal Data](http://aclweb.org/anthology/P16-1169)
- \[COLING 2016\] [Revisiting Taxonomy Induction over Wikipedia](http://www.aclweb.org/anthology/C16-1217)
- \[CIKM 2017\] [Taxonomy Induction using Hypernym Subsequences](https://arxiv.org/pdf/1704.07626.pdf)
- \[NAACL 2018 \] [Comparing Constraints for Taxonomic Organization](https://www.aclweb.org/anthology/N18-1030)
* Code: [https://github.com/acocos/tax-org](https://github.com/acocos/tax-org)
- \[KDD 2018\] [HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion](http://hanj.cs.illinois.edu/pdf/kdd18_jshen.pdf)
* Code: [https://github.com/mickeystroller/HiExpan](https://github.com/mickeystroller/HiExpan)
- \[ACL 2018\] [End-to-End Reinforcement Learning for Automatic Taxonomy Induction](http://aclweb.org/anthology/P18-1229)
* Code: [https://github.com/morningmoni/TaxoRL](https://github.com/morningmoni/TaxoRL)
- \[ACL 2019\] [Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings](https://arxiv.org/pdf/1902.00913.pdf)
- \[ACL 2020\] [Taxonomy Construction of Unseen Domains via Graph-based Cross-Domain Knowledge Transfer]()
* Code: [https://github.com/IBM/gnn-taxo-construction](https://github.com/IBM/gnn-taxo-construction)
- \[NAACL 2021\] [Constructing Taxonomies from Pretrained Language Models](https://www.aclweb.org/anthology/2021.naacl-main.373.pdf)
* Code: [https://github.com/cchen23/ctp](https://github.com/cchen23/ctp)
- \[SEM 2022\] [Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction](https://aclanthology.org/2022.starsem-1.13.pdf)
* Code: [https://github.com/devanshrj/zero-shot-taxonomy](https://github.com/devanshrj/zero-shot-taxonomy)
- \[Arxiv 2024\] [Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples](https://arxiv.org/pdf/2402.07386.pdf)
* Code: [https://github.com/QingkaiZeng/Chain-of-Layer](https://github.com/QingkaiZeng/Chain-of-Layer)## Topic Taxonomy Construction (Clustering-based Taxonomy)
- \[KDD 2012\] [Automatic Taxonomy Construction from Keywords](http://cgcad.thss.tsinghua.edu.cn/shixia/publications/brt/paper.pdf)
- \[KDD 2013\] [A Phrase Mining Framework for Recursive Construction of a Topical Hierarchy](https://uofi.app.box.com/v/kdd13-cathy)
- \[ACL 2015\] [Efficient Methods for Inferring Large Sparse Topic Hierarchies](http://aclweb.org/anthology/P15-1075)
- \[KDD 2018\] [TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering](http://hanj.cs.illinois.edu/pdf/kdd18_czhang.pdf)
* Code: [https://github.com/franticnerd/taxogen](https://github.com/franticnerd/taxogen)
- \[WWW 2020\] [NetTaxo: Automated Topic Taxonomy Construction from Text-Rich Network](http://hanj.cs.illinois.edu/pdf/www20_jshang.pdf)
- \[KDD 2020\] [CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring](https://dl.acm.org/doi/10.1145/3394486.3403244)
* Code: [https://github.com/teapot123/CoRel](https://github.com/teapot123/CoRel)## Taxonomy Expansion & Enrichment
- \[CIKM 2012\] [A graph-based approach for ontology population with named entities](https://dl.acm.org/citation.cfm?doid=2396761.2396807)
- \[WWW 2014\] [A Hierarchical Dirichlet Model for Taxonomy Expansion for Search Engines](http://yichang-cs.com/yahoo/www14_local.pdf)
- \[NAACL 2015\] [Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms](https://www.aclweb.org/anthology/N15-1169)
- \[SemEval 2016\] [SemEval-2016 Task 14: Semantic Taxonomy Enrichment](https://www.aclweb.org/anthology/S16-1169)
- \[SIGIR 2018\] [Enriching Taxonomies With Functional Domain Knowledge](https://dl.acm.org/doi/10.1145/3209978.3210000)
- \[ACL 2019\] [Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings](https://www.aclweb.org/anthology/P19-1474/)
* Code: [https://github.com/uhh-lt/Taxonomy_Refinement_Embeddings](https://github.com/uhh-lt/Taxonomy_Refinement_Embeddings)
- \[ACL 2019\] [Automatic Taxonomy Induction and Expansion](https://www.aclweb.org/anthology/D19-3005.pdf)
- \[AKBC 2019\] [Synonym Expansion for Large Shopping Taxonomies](https://openreview.net/pdf?id=rJx2g-qaTm)
- \[WWW 2020\] [Expanding Taxonomies with Implicit Edge Semantics](http://emaadmanzoor.com/papers/20-www-arborist.pdf)
* Website w/ code, slides, video, etc.: [https://cmuarborist.github.io/](https://cmuarborist.github.io/)
- \[WWW 2020\] [TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network](https://arxiv.org/abs/2001.09522)
* Code: [https://github.com/mickeystroller/TaxoExpan](https://github.com/mickeystroller/TaxoExpan)
- \[KDD 2020\] [STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths](https://arxiv.org/pdf/2006.10217.pdf)
* Code: [https://github.com/yueyu1030/STEAM](https://github.com/yueyu1030/STEAM)
- \[KDD 2020\] [Octet: Online Catalog Taxonomy Enrichment with Self-Supervision](https://arxiv.org/abs/2006.10276)
- \[WWW-SSL 2021\] [Who Should Go First? A Self-Supervised Concept Sorting Model for Improving Taxonomy Expansion](https://arxiv.org/pdf/2104.03682.pdf)
- \[AAAI 2021\] [Taxonomy Completion via Triplet Matching Network](https://arxiv.org/pdf/2101.01896.pdf)
* Code: [https://github.com/JieyuZ2/TMN](https://github.com/JieyuZ2/TMN)
- \[KDD 2021\] [Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations](https://arxiv.org/pdf/2106.02974.pdf)
* Code: [https://github.com/QingkaiZeng/GenTaxo](https://github.com/QingkaiZeng/GenTaxo)
- \[WWW 2021\] [Enquire One’s Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansion](https://arxiv.org/pdf/2101.11268.pdf)
* Code: [https://github.com/sheryc/HEF](https://github.com/sheryc/HEF)
- \[EMNLP 2021\] [TEMP: Taxonomy Expansion with Dynamic Margin Loss through Taxonomy-Paths](https://aclanthology.org/2021.emnlp-main.313)
- \[EMNLP 2021\] [Low-resource Taxonomy Enrichment with Pretrained Language Models](https://aclanthology.org/2021.emnlp-main.217/)
- \[EMNLP Findings 2021\] [HyperExpan: Taxonomy Expansion with Hyperbolic Representation Learning](https://arxiv.org/pdf/2109.10500.pdf)
- \[WWW 2022\] [TaxoEnrich: Self-Supervised Taxonomy Completion via Structure-Semantic Representations](https://arxiv.org/pdf/2202.04887.pdf)
- \[WWW 2022\] [QEN: Applicable Taxonomy Completion via Evaluating Full Taxonomic Relations](https://dl.acm.org/doi/abs/10.1145/3485447.3511943)
- \[WWW 2022\] [TaxoCom: Topic Taxonomy Completion with Hierarchical Discovery of Novel Topic Clusters](https://arxiv.org/pdf/2201.06771.pdf)
- \[ICDE 2022\] [Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervision](https://arxiv.org/pdf/2203.14921.pdf)
* Code: [https://github.com/AdaCheng/Product_Taxonomy_Expansion](https://github.com/AdaCheng/Product_Taxonomy_Expansion)
- \[Semantic Web 2022\] [Taxonomy enrichment with text and graph vector representations](https://arxiv.org/pdf/2201.08598.pdf)
- \[NAACL 2022\] [TEAM: A multitask learning based Taxonomy Expansion approach for Attach and Merge](https://aclanthology.org/2022.findings-naacl.28.pdf)
- \[IJCAI 2022\] [TaxoPrompt: A Prompt-based Generation Method with Taxonomic Context for Self-Supervised Taxonomy Expansion](https://www.ijcai.org/proceedings/2022/0615.pdf)
- \[EMNLP 2022\] [Topic Taxonomy Expansion via Hierarchy-Aware Topic Phrase Generation](https://aclanthology.org/2022.findings-emnlp.122.pdf)
- \[AAAI 2023\] [DNG: Taxonomy Expansion by Exploring the Intrinsic Directed Structure on Non-Gaussian Space](https://arxiv.org/pdf/2302.11165.pdf)
- \[WWW 2023\] [A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings](https://songjiang0909.github.io/pdf/boxtaxo.pdf)
* Code: [https://github.com/songjiang0909/BoxTaxo](https://github.com/songjiang0909/BoxTaxo)
- \[WWW 2023\] [TaxoComplete: Self-Supervised Taxonomy Completion Leveraging Position-Enhanced Semantic Matching](https://dl.acm.org/doi/pdf/10.1145/3543507.3583342)
* Code: [https://github.com/eXascaleInfolab/TaxoComplete](https://github.com/eXascaleInfolab/TaxoComplete)
- \[EACL 2023\] [Find Parent then Label Children: A Two-stage Taxonomy Completion Method with Pre-trained Language Model](https://aclanthology.org/2023.eacl-main.73.pdf)
* Code: [https://github.com/WENGSYX/ATTEMPT](https://github.com/WENGSYX/ATTEMPT)
- \[EMNLP 2023\] [TacoPrompt: A Collaborative Multi-Task Prompt Learning Method for Self-Supervised Taxonomy Completion](https://aclanthology.org/2023.emnlp-main.979.pdf)
* Code: [https://github.com/cyclexu/TacoPrompt](https://github.com/cyclexu/TacoPrompt)
- \[MM 2023\] [Towards Visual Taxonomy Expansion](https://arxiv.org/pdf/2309.06105.pdf)
* Code: [https://github.com/darthzhu/vte](https://github.com/darthzhu/vte)
- \[WebConf 2024\] [Taxonomy Completion via Implicit Concept Insertion](https://ora.ox.ac.uk/objects/uuid:734f4f2c-e8de-4778-8902-6776b099b7b0/files/s6q182m86q)
* Code: [https://github.com/jingcshi/ICON](https://github.com/jingcshi/ICON)
* Talk: [https://www.youtube.com/watch?v=9otF15bvuBc](https://www.youtube.com/watch?v=9otF15bvuBc)## Taxonomy Applications
### Help Text Understanding and Representation Learning
- \[SIGMOD 2012\] [Probase: A probabilistic taxonomy for text understanding](https://www.microsoft.com/en-us/research/wp-content/uploads/2012/05/paper.pdf)
- \[KDD 2019\] [Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts](http://web.cs.ucla.edu/~yzsun/papers/2019_KDD_JOIE.pdf)
* Code: [https://github.com/JunhengH/joie-kdd19](https://github.com/JunhengH/joie-kdd19)
- \[AKBC 2021\] [Manifold Alignment across Geometric Spaces for Knowledge Base Representation Learning](https://openreview.net/pdf?id=TPymTKJR-Pi)
* Code: [https://github.com/HKUST-KnowComp/GeoAlign](https://github.com/HKUST-KnowComp/GeoAlign)### Help Information Retrieval
- \[WebConf 2024\] [Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy](https://arxiv.org/pdf/2403.04160)
* Code: [https://github.com/SeongKu-Kang/ToTER_WWW24](https://github.com/SeongKu-Kang/ToTER_WWW24)
* Talk: [https://www.youtube.com/watch?v=Y7RU5GpgaEI](https://www.youtube.com/watch?v=Y7RU5GpgaEI)### Help Network Embedding
- \[KDD 2018\] [Hierarchical Taxonomy Aware Network Embedding](http://pengcui.thumedialab.com/papers/NE-Hierarchical.pdf)
- \[KDD 2018\] [On Interpretation of Network Embedding via Taxonomy Induction](http://www.public.asu.edu/~jundongl/paper/KDD18_Network_Embedding_Interpretation.pdf)
* Code: [https://github.com/ninghaohello/UnderstandingNetworkEmbedding](https://github.com/ninghaohello/UnderstandingNetworkEmbedding)
- \[ICDM 2020\] [Co-Embedding Network Nodes and Hierarchical Labels with Taxonomy Based Generative Adversarial Networks](https://jiyang3.web.engr.illinois.edu/files/taxogan.pdf)
* Code: [https://github.com/JieyuZ2/TaxoGAN](https://github.com/JieyuZ2/TaxoGAN)### Improve Recommender System
- \[CIKM 2004\] [Taxonomy-driven computation of product recommendations](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.90.3304&rep=rep1&type=pdf)
- \[VLDB 2012\] [Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior](https://arxiv.org/abs/1207.0136)
- \[WSDM 2014\] [Taxonomy Discovery for Personalized Recommendation](https://ai.google/research/pubs/pub42499)
- \[WSDM 2019\] [Taxonomy-Aware Multi-Hop Reasoning Networks for Sequential Recommendation](https://dl.acm.org/citation.cfm?id=3290972)
* Code: [https://github.com/RUCDM/TMRN](https://github.com/RUCDM/TMRN)
- \[KDD 2019\] [A User-Centered Concept Mining System for Query and Document Understanding at Tencent ](https://arxiv.org/pdf/1905.08487.pdf)
* Code: [https://github.com/BangLiu/ConcepT](https://github.com/BangLiu/ConcepT)
* Code: [https://github.com/JunhengH/joie-kdd19](https://github.com/JunhengH/joie-kdd19)
- \[CIKM 2019\] [STAR: Spatio-Temporal Taxonomy-Aware Tag Recommendation for Citizen Complaints](https://www.microsoft.com/en-us/research/uploads/prod/2019/10/lp0249-gaoA.pdf)
* Code: [https://github.com/jygao97/STAR](https://github.com/jygao97/STAR)
- \[ICDE 2022\] [Enhancing Recommendation with Automated Tag Taxonomy Construction in Hyperbolic Space](https://www.cs.emory.edu/~jyang71/files/taxorec.pdf)
* Code: [https://github.com/Melinda315/TaxoRec](https://github.com/Melinda315/TaxoRec)### Improve Information Extraction
- \[ACL 2020\] [TXtract: Taxonomy-Aware Knowledge Extraction for Thousands of Product Categories](https://arxiv.org/pdf/2004.13852.pdf)
- \[ACL 2021\] [OntoED: Low-resource Event Detection with Ontology Embedding](https://arxiv.org/pdf/2105.10922.pdf)
* Code: [https://github.com/231sm/Reasoning_In_EE](https://github.com/231sm/Reasoning_In_EE)
- \[ACL 2021\] [OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embedding](https://arxiv.org/pdf/2105.07688.pdf)
* Code: [https://github.com/ZihengZZH/OntoEA](https://github.com/ZihengZZH/OntoEA)
- \[EMNLP 2021\] [ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-Guided Distant Supervision](https://aclanthology.org/2021.emnlp-main.424.pdf)
* Code: [https://github.com/xuanwang91/ChemNER](https://github.com/xuanwang91/ChemNER)
- \[WWW 2022\] [Ontology-enhanced Prompt-tuning for Few-shot Learning](https://arxiv.org/pdf/2201.11332.pdf)
- \[EMNLP 2023\] [Taxonomy Expansion for Named Entity Recognition](https://aclanthology.org/2023.emnlp-main.426.pdf)### Guide Entity Translation
- \[KDD 2022\] [TaxoTrans: Taxonomy-Guided Entity Translation](https://dl.acm.org/doi/abs/10.1145/3534678.3539188)
## Joint Taxonomy Construction and Application
- \[EMNLP 2012\] [Constructing Task-Specific Taxonomies for Document Collection Browsing](http://aclweb.org/anthology/D12-1117)
- \[WWW 2019\] [TiFi: Taxonomy Induction for Fictional Domains](https://arxiv.org/pdf/1901.10263.pdf)
- \[SIGMOD 2020\] [GIANT: Scalable Creation of a Web-scale Ontology](https://arxiv.org/pdf/2004.02118.pdf)
* Code: [https://github.com/BangLiu/GIANT](https://github.com/BangLiu/GIANT)## Misc
- \[ACL 2022\] [CogTaskonomy: Cognitively Inspired Task Taxonomy Is Beneficial to Transfer Learning in NLP](https://paperswithcode.com/paper/cogtaskonomy-cognitively-inspired-task)
- \[ACL 2022\] [Better Language Model with Hypernym Class Prediction ](https://arxiv.org/pdf/2203.10692.pdf)
* Code: [https://github.com/richardbaihe/robustLM](https://github.com/richardbaihe/robustLM)
- \[ACL 2023\] [ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain](https://aclanthology.org/2023.acl-long.662.pdf)
* Code: [https://github.com/mainlp/escoxlmr](https://github.com/mainlp/escoxlmr)