skip to main content
10.1145/3477495.3531944acmconferencesArticle/Chapter ViewAbstractPublication PagesirConference Proceedingsconference-collections
research-article
Public Access

BERT-ER: Query-specific BERT Entity Representations for Entity Ranking

Published: 07 July 2022 Publication History

Abstract

Entity-oriented search systems often learn vector representations of entities via the introductory paragraph from the Wikipedia page of the entity. As such representations are the same for every query, our hypothesis is that the representations are not ideal for IR tasks. In this work, we present BERT Entity Representations (BERT-ER) which are query-specific vector representations of entities obtained from text that describes how an entity is relevant for a query. Using BERT-ER in a downstream entity ranking system, we achieve a performance improvement of 13-42% (Mean Average Precision) over a system that uses the BERT embedding of the introductory paragraph from Wikipedia on two large-scale test collections. Our approach also outperforms entity ranking systems using entity embeddings from Wikipedia2Vec, ERNIE, and E-BERT. We show that our entity ranking system using BERT-ER can increase precision at the top of the ranking by promoting relevant entities to the top. With this work, we release our BERT models and query-specific entity embeddings fine-tuned for the entity ranking task.

References

[1]
Krisztian Balog, Marc Bron, and Maarten De Rijke. 2011. Query Modeling for Entity Search Based on Terms, Categories, and Examples. ACM Transactions on Information Systems 29, 4, Article 22 (Dec. 2011), 31 pages. https://doi.org/10. 1145/2037661.2037667
[2]
Krisztian Balog, Pavel Serdyukov, and Arjen P. de Vries. 2010. Overview of the TREC 2010 Entity Track. Technical Report. Norwegian University of Science and Technology.
[3]
Roi Blanco, Harry Halpin, Daniel M Herzig, Peter Mika, Jeffrey Pound, Henry S Thompson, and T Tran Duc. 2011. Entity Search Evaluation Over Structured Web Data. In Proceedings of the 1st International Workshop on Entity-oriented Search (Beijing, China) (SIGIR '11, Vol. 14). Association for Computing Machinery, New York, NY, USA, 2181--2187.
[4]
Roi Blanco and Hugo Zaragoza. 2010. Finding Support Sentences for Entities. In Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval (Geneva, Switzerland) (SIGIR '10). Association for Computing Machinery, New York, NY, USA, 339--346. https://doi.org/10.1145/1835449.1835507
[5]
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Durán, Jason Weston, and Oksana Yakhnenko. 2013. Translating Embeddings for Modeling Multi-Relational Data. In Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 2 (Lake Tahoe, Nevada) (NIPS'13). Curran Associates Inc., Red Hook, NY, USA, 2787--2795.
[6]
Marc Bron, Krisztian Balog, and Maarten de Rijke. 2013. Example Based Entity Search in the Web of Data. In Advances in Information Retrieval, Proceedings of the 35th European Conference on IR Research (ECIR 2013) (Moscow, Russia) (Lecture Notes in Computer Science). Springer, Berlin, Heidelberg, 392--403. https: //doi.org/10.1007/978--3--642--36973--5_33
[7]
T. Cali'ski and J. Harabasz. 1974. A Dendrite Method for Cluster Analysis. Communications in Statistics 3, 1 (1974), 1--27. https://doi.org/10.1080/ 03610927408827101
[8]
Shubham Chatterjee and Laura Dietz. 2019. Why Does This Entity Matter? Support Passage Retrieval for Entity Retrieval. In Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval (Santa Clara, CA, USA) (ICTIR '19). Association for Computing Machinery, New York, NY, USA, 221--224. https://doi.org/10.1145/3341981.3344243
[9]
Shubham Chatterjee and Laura Dietz. 2021. Entity Retrieval Using Fine-Grained Entity Aspects. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (Virtual Event, Canada) (SIGIR '21). Association for Computing Machinery, New York, NY, USA, 1662--1666. https://doi.org/10.1145/3404835.3463035
[10]
Marek Ciglan, Kjetil Nørvåg, and Ladislav Hluchý. 2012. The SemSets Model for Ad-Hoc Semantic List Search. In Proceedings of the 21st International Conference on World Wide Web (Lyon, France) (WWW '12). Association for Computing Machinery, New York, NY, USA, 131--140. https://doi.org/10.1145/2187836.2187855
[11]
Jeffrey Dalton, Laura Dietz, and James Allan. 2014. Entity Query Feature Expansion Using Knowledge Base Links. In Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (Gold Coast, Queensland, Australia) (SIGIR '14). Association for Computing Machinery, New York, NY, USA, 365--374. https://doi.org/10.1145/2600428.2609628
[12]
David L. Davies and Donald W. Bouldin. 1979. A Cluster Separation Measure. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-1, 2 (1979), 224--227. https://doi.org/10.1109/TPAMI.1979.4766909
[13]
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, Minneapolis, Minnesota, 4171--4186. https://doi.org/10.18653/v1/N19--1423
[14]
Laura Dietz. 2019. ENT Rank: Retrieving Entities for Topical Information Needs through Entity-Neighbor-Text Relations. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (Paris, France) (SIGIR'19). Association for Computing Machinery, New York, NY, USA, 215--224. https://doi.org/10.1145/3331184.3331257
[15]
Laura Dietz and John Foley. 2019. TREC CAR Y3: Complex Answer Retrieval Overview. In Proceedings of Text REtrieval Conference (TREC).
[16]
Laura Dietz, Michael Schuhmacher, and Simone Paolo Ponzetto. 2014. Queripidia: Query-specific Wikipedia Construction. Proceedings of the Automatic Knowledge Base Construction (AKBC) Workshop (2014).
[17]
Paolo Ferragina and Ugo Scaiella. 2010. TAGME: On-the-Fly Annotation of Short Text Fragments (by Wikipedia Entities). In Proceedings of the 19th ACM International Conference on Information and Knowledge Management (Toronto, ON, Canada) (CIKM '10). Association for Computing Machinery, New York, NY, USA, 1625--1628. https://doi.org/10.1145/1871437.1871689
[18]
Besnik Fetahu, Katja Markert, and Avishek Anand. 2015. Automated News Suggestions for Populating Wikipedia Entity Pages. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (Melbourne, Australia) (CIKM '15). Association for Computing Machinery, New York, NY, USA, 323--332. https://doi.org/10.1145/2806416.2806531
[19]
Octavian-Eugen Ganea and Thomas Hofmann. 2017. Deep Joint Entity Disambiguation with Local Neural Attention. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, Copenhagen, Denmark, 2619--2629. https://doi.org/10.18653/v1/D17- 1277
[20]
Emma J Gerritse, Faegheh Hasibi, and Arjen P de Vries. 2020. Graph-Embedding Empowered Entity Retrieval. In Advances in Information Retrieval, Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020) (Lisbon, Portugal) (Lecture Notes in Computer Science). Springer, Cham, 97--110. https: //doi.org/10.1007/978--3-030--45439--5_7
[21]
David Graus, Manos Tsagkias, Wouter Weerkamp, Edgar Meij, and Maarten de Rijke. 2016. Dynamic Collective Entity Representations for Entity Ranking. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (San Francisco, California, USA) (WSDM '16). Association for Computing Machinery, New York, NY, USA, 595--604. https://doi.org/10.1145/2835776.2835819
[22]
Faegheh Hasibi, Krisztian Balog, and Svein Erik Bratsberg. 2016. Exploiting Entity Linking in Queries for Entity Retrieval. In Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval (Newark, Delaware, USA) (ICTIR '16). Association for Computing Machinery, New York, NY, USA, 209--218. https://doi.org/10.1145/2970398.2970406
[23]
Faegheh Hasibi, Fedor Nikolaev, Chenyan Xiong, Krisztian Balog, Svein Erik Bratsberg, Alexander Kotov, and Jamie Callan. 2017. DBpedia-Entity v2: A Test Collection for Entity Search. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (Shinjuku, Tokyo, Japan) (SIGIR '17). Association for Computing Machinery, New York, NY, USA, 1265--1268. https://doi.org/10.1145/3077136.3080751
[24]
Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao. 2015. Knowledge Graph Embedding via Dynamic Mapping Matrix. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, Beijing, China, 687--696. https://doi.org/10.3115/v1/P15--1067
[25]
Amina Kadry and Laura Dietz. 2017. Open Relation Extraction for Support Passage Retrieval: Merit and Open Issues. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (Shinjuku, Tokyo, Japan) (SIGIR '17). Association for Computing Machinery, New York, NY, USA, 1149--1152. https://doi.org/10.1145/3077136.3080744
[26]
Rianne Kaptein and Jaap Kamps. 2013. Exploiting the Category Structure of Wikipedia for Entity Ranking. Artificial Intelligence 194 (Jan. 2013), 111--129. https://doi.org/10.1016/j.artint.2012.06.003
[27]
Rianne Kaptein, Pavel Serdyukov, Arjen De Vries, and Jaap Kamps. 2010. Entity Ranking Using Wikipedia as a Pivot. In Proceedings of the 19th ACM International Conference on Information and Knowledge Management (Toronto, ON, Canada) (CIKM '10). Association for Computing Machinery, New York, NY, USA, 69--78. https://doi.org/10.1145/1871437.1871451
[28]
Aniruddha Kembhavi, Minjoon Seo, Dustin Schwenk, Jonghyun Choi, Ali Farhadi, and Hannaneh Hajishirzi. 2017. Are You Smarter Than a Sixth Grader? Textbook Question Answering for Multimodal Machine Comprehension. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4999--5007.
[29]
Diederik P Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:1412.6980 (2014).
[30]
Oren Kurland. 2014. The Cluster Hypothesis in Information Retrieval. In Advances in Information Retrieval, Proceedings of the 36th European Conference on IR Research (ECIR 2014) (Amsterdam, The Netherlands) (Lecture Notes in Computer Science). Springer, 823--826. https://doi.org/10.1007/978--3--319-06028--6_105
[31]
Victor Lavrenko and W. Bruce Croft. 2001. Relevance-Based Language Models. SIGIR Forum 51, 2 (Aug. 2001), 260--267. https://doi.org/10.1145/3130348.3130376
[32]
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, Sören Auer, et al. 2012. DBpedia--A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia. Semantic Web Journal 6, 2 (2012), 167--195. https: //doi.org/10.3233/SW-140134
[33]
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015. Learning Entity and Relation Embeddings for Knowledge Graph Completion. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (Austin, Texas) (AAAI'15). AAAI Press, 2181--2187.
[34]
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. CoRR abs/1907.11692 (2019). arXiv:1907.11692 http://arxiv.org/abs/1907.11692
[35]
Zhenghao Liu, Chenyan Xiong, Maosong Sun, and Zhiyuan Liu. 2018. EntityDuet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Melbourne, Australia, 2395--2405. https://doi.org/10. 18653/v1/P18--1223
[36]
Jarana Manotumruksa, Jeff Dalton, Edgar Meij, and Emine Yilmaz. 2020. CrossBERT: A Triplet Neural Architecture for Ranking Entity Properties. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (Virtual Event, China) (SIGIR '20). Association for Computing Machinery, New York, NY, USA, 2049--2052. https: //doi.org/10.1145/3397271.3401265
[37]
Donald Metzler and W. Bruce Croft. 2005. A Markov Random Field Model for Term Dependencies. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Salvador, Brazil) (SIGIR '05). Association for Computing Machinery, New York, NY, USA, 472--479. https://doi.org/10.1145/1076034.1076115
[38]
Tomas Mikolov, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013. Efficient Estimation of Word Representations in Vector Space. In Proceedings of the 2013 International Conference on Learning Representations.
[39]
Tomas Mikolov, Ilya Sutskever, Kai Chen, Gregory S., and Jeffrey Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. In Advances in Neural Information Processing Systems.
[40]
Federico Nanni, Simone Paolo Ponzetto, and Laura Dietz. 2018. Entity-Aspect Linking: Providing Fine-Grained Semantics of Entities in Context. In Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (Fort Worth, Texas, USA) (JCDL '18). Association for Computing Machinery, New York, NY, USA, 49--58. https://doi.org/10.1145/3197026.3197047
[41]
Fedor Nikolaev, Alexander Kotov, and Nikita Zhiltsov. 2016. Parameterized Fielded Term Dependence Models for Ad-Hoc Entity Retrieval from Knowledge Graph. In Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (Pisa, Italy) (SIGIR '16). Association for Computing Machinery, New York, NY, USA, 435--444. https://doi.org/10.1145/ 2911451.2911545
[42]
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019. Multi-Stage Document Ranking with BERT. CoRR abs/1910.14424 (2019). arXiv:1910.14424 http://arxiv.org/abs/1910.14424
[43]
Matthew E. Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A. Smith. 2019. Knowledge Enhanced Contextual Word Representations. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, 43--54. https://doi.org/10.18653/v1/D19--1005
[44]
Nina Poerner, Ulli Waltinger, and Hinrich Schütze. 2020. E-BERT: Efficient-YetEffective Entity Embeddings for BERT. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 803--818. https://doi.org/10.18653/v1/2020.findings-emnlp.71
[45]
Marco Ponza, Paolo Ferragina, and Francesco Piccinno. 2018. SWAT: A System for Detecting Salient Wikipedia Entities in Texts. Computational Intelligence (04 2018). https://doi.org/10.1111/coin.12216
[46]
Jordan Ramsdell and Laura Dietz. 2020. A Large Test Collection for Entity Aspect Linking. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (Virtual Event, Ireland) (CIKM '20). Association for Computing Machinery, New York, NY, USA, 3109--3116. https://doi.org/10.1145/ 3340531.3412875
[47]
Hadas Raviv, David Carmel, and Oren Kurland. 2012. A Ranking Framework for Entity Oriented Search Using Markov Random Fields. In Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search (Portland, Oregon, USA) (JIWES '12). Association for Computing Machinery, New York, NY, USA, Article 1, 6 pages. https://doi.org/10.1145/2379307.2379308
[48]
Ridho Reinanda, Edgar Meij, and Maarten de Rijke. 2016. Document Filtering for Long-Tail Entities. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (Indianapolis, Indiana, USA) (CIKM '16). Association for Computing Machinery, New York, NY, USA, 771--780. https: //doi.org/10.1145/2983323.2983728
[49]
Stephen Robertson and Hugo Zaragoza. 2009. The probabilistic relevance framework: BM25 and beyond. Now Publishers Inc.
[50]
Peter J. Rousseeuw. 1987. Silhouettes: A Graphical Aid to the Interpretation and Validation of Cluster Analysis. J. Comput. Appl. Math. 20 (1987), 53--65. https://doi.org/10.1016/0377-0427(87)90125--7
[51]
Andrew Runge and Eduard Hovy. 2020. Exploring Neural Entity Representations for Semantic Information. In Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP. Association for Computational Linguistics, Online, 204--216. https://doi.org/10.18653/v1/2020. blackboxnlp-1.20
[52]
Michael Schuhmacher, Laura Dietz, and Simone Paolo Ponzetto. 2015. Ranking Entities for Web Queries Through Text and Knowledge. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (Melbourne, Australia) (CIKM '15). Association for Computing Machinery, New York, NY, USA, 1461--1470. https://doi.org/10.1145/2806416.2806480
[53]
Alberto Tonon, Gianluca Demartini, and Philippe Cudré-Mauroux. 2012. Combining Inverted Indices and Structured Search for Ad-Hoc Object Retrieval. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval (Portland, Oregon, USA) (SIGIR '12). Association for Computing Machinery, New York, NY, USA, 125--134. https: //doi.org/10.1145/2348283.2348304
[54]
Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing Data Using t-SNE. Journal of Machine Learning Research 9, 11 (2008).
[55]
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhengyan Zhang, Zhiyuan Liu, Juanzi Li, and Jian Tang. 2021. KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation. Transactions of the Association for Computational Linguistics 9 (2021), 176--194. https://doi.org/10.1162/tacl_a_00360
[56]
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014. Knowledge Graph Embedding by Translating on Hyperplanes. In Proceedings of the TwentyEighth AAAI Conference on Artificial Intelligence (Québec City, Québec, Canada) (AAAI'14). AAAI Press, 1112--1119.
[57]
Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, and Maosong Sun. 2016. Representation Learning of Knowledge Graphs with Entity Descriptions. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (Phoenix, Arizona) (AAAI'16). AAAI Press, 2659--2665.
[58]
Chenyan Xiong, Russell Power, and Jamie Callan. 2017. Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding. In Proceedings of the 26th International Conference on World Wide Web (Perth, Australia) (WWW '17). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE, 1271--1279. https://doi.org/10.1145/3038912.3052558
[59]
Ikuya Yamada, Akari Asai, Jin Sakuma, Hiroyuki Shindo, Hideaki Takeda, Yoshiyasu Takefuji, and Yuji Matsumoto. 2020. Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Association for Computational Linguistics, 23--30.
[60]
Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, and Yoshiyasu Takefuji. 2016. Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation. In Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning. Association for Computational Linguistics, Berlin, Germany, 250--259. https://doi.org/10.18653/v1/K16--1025
[61]
Ikuya Yamada, Hiroyuki Shindo, and Yoshiyasu Takefuji. 2018. Representation Learning of Entities and Documents from Knowledge Base Descriptions. In Proceedings of the 27th International Conference on Computational Linguistics. Association for Computational Linguistics, Santa Fe, New Mexico, USA, 190--201. https://aclanthology.org/C18--1016
[62]
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019. ERNIE: Enhanced Language Representation with Informative Entities. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, 1441--1451. https://doi.org/10.18653/v1/P19--1139
[63]
Nikita Zhiltsov, Alexander Kotov, and Fedor Nikolaev. 2015. Fielded Sequential Dependence Model for Ad-Hoc Entity Retrieval in the Web of Data. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (Santiago, Chile) (SIGIR '15). Association for Computing Machinery, New York, NY, USA, 253--262. https://doi.org/10.1145/2766462.2767756

Cited By

View all
  • (2024)Bir İnsan Bilgisayar Etkileşimi Örneği: Sesli Komutlar İle Veri Tabanı Sorgulama UygulamasıKaradeniz Fen Bilimleri Dergisi10.31466/kfbd.138440114:1(211-223)Online publication date: 15-Mar-2024
  • (2024)A Knowledge Graph Embedding Model for Answering Factoid Entity QuestionsACM Transactions on Information Systems10.1145/3678003Online publication date: 15-Jul-2024
  • (2024)The First Workshop on Evaluation Methodologies, Testbeds and Community for Information Access Research (EMTCIR 2024)Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3673791.3698434(311-314)Online publication date: 8-Dec-2024
  • Show More Cited By

Index Terms

  1. BERT-ER: Query-specific BERT Entity Representations for Entity Ranking

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
      July 2022
      3569 pages
      ISBN:9781450387323
      DOI:10.1145/3477495
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 07 July 2022

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. bert
      2. entity ranking
      3. query-specific entity representations

      Qualifiers

      • Research-article

      Funding Sources

      Conference

      SIGIR '22
      Sponsor:

      Acceptance Rates

      Overall Acceptance Rate 792 of 3,983 submissions, 20%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)250
      • Downloads (Last 6 weeks)31
      Reflects downloads up to 28 Feb 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Bir İnsan Bilgisayar Etkileşimi Örneği: Sesli Komutlar İle Veri Tabanı Sorgulama UygulamasıKaradeniz Fen Bilimleri Dergisi10.31466/kfbd.138440114:1(211-223)Online publication date: 15-Mar-2024
      • (2024)A Knowledge Graph Embedding Model for Answering Factoid Entity QuestionsACM Transactions on Information Systems10.1145/3678003Online publication date: 15-Jul-2024
      • (2024)The First Workshop on Evaluation Methodologies, Testbeds and Community for Information Access Research (EMTCIR 2024)Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3673791.3698434(311-314)Online publication date: 8-Dec-2024
      • (2024)Benchmark and Neural Architecture for Conversational Entity Retrieval from a Knowledge GraphProceedings of the ACM Web Conference 202410.1145/3589334.3645676(1519-1528)Online publication date: 13-May-2024
      • (2024)Learning contextual representations for entity retrievalApplied Intelligence10.1007/s10489-024-05430-054:19(8820-8840)Online publication date: 4-Jul-2024
      • (2024)Generating Entity Embeddings for Populating Wikipedia Knowledge Graph by Notability DetectionNatural Language Processing and Information Systems10.1007/978-3-031-70242-6_2(10-23)Online publication date: 20-Sep-2024
      • (2024)DREQ: Document Re-ranking Using Entity-Based Query UnderstandingAdvances in Information Retrieval10.1007/978-3-031-56027-9_13(210-229)Online publication date: 24-Mar-2024
      • (2024)Potential for artificial intelligence in medicine and its application to male infertilityReproductive Medicine and Biology10.1002/rmb2.1259023:1Online publication date: 28-Jun-2024
      • (2023)Multimodal Dialog Systems with Dual Knowledge-enhanced Generative Pretrained Language ModelACM Transactions on Information Systems10.1145/360636842:2(1-25)Online publication date: 6-Oct-2023
      • (2023)Answering Topical Information Needs Using Neural Entity-Oriented Information Retrieval and ExtractionACM SIGIR Forum10.1145/3582900.358292656:2(1-2)Online publication date: 31-Jan-2023
      • Show More Cited By

      View Options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Login options

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media