The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
KATIE: A System for Key Attributes Identification in Product Knowledge Graph Construction
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In the citing paper
“User intents are a crucial source of information for E-Commerce (Deng et al., 2023;Er-Rahmadi et al., 2023;Zhang et al., 2016;Hao et al., 2022).”
From A Usage-centric Take on Intent Understanding in E-Commerce (2024) · cites this paper as Er-Rahmadi et al., 2023
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Citations
Cites
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Sanh, V., Debut, L., Chaumond, J., & Wolf, T. (2019) · arXiv · doi:10.48550/arxiv.1910.01108 · Cited by 4,653
Towards Competency Question-Driven Ontology Authoring
Ren, Y., Parvizi, A., Mellish, C., Pan, J. Z., van Deemter, K., & Stevens, R. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-07443-6_50 · Cited by 126
Self-citation
Research works printed but not linked: 21
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- Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, and Jeff Z. Pan. 2022. Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs. In Proc. of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 22). 3078--3084.
- Saratchandra Indrakanti and Gyanit Singh. 2018. A Framework to Discover Significant Product Aspects from e-Commerce Product Reviews. In eCOM@SIGIR.
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- Ilya Loshchilov and Frank Hutter. 2019. DecoupledWeight Decay Regularization. http://arxiv.org/abs/1711.05101 arXiv:1711.05101 [cs math]. · arXiv
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- Karin Mauge, Khash Rohanimanesh, and Jean-David Ruvini. 2012. Structuring ecommerce inventory. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1 (ACL '12). Association for Computational Linguistics, USA, 805--814.
- Chris Mellish and Jeff Z. Pan. 2008. Natural Language Directed Inference from Ontologie". In Artificial Intelligence Journal.
- Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin. 2018. Advances in Pre-Training Distributed Word Representations. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). European Language Resources Association (ELRA), Miyazaki, Japan, 52--55. https://aclanthology.org/L18-1008
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- Chi Sun, Xipeng Qiu, Yige Xu, and Xuanjing Huang. 2019. How to Fine-Tune BERT for Text Classification?. In Chinese Computational Linguistics, Maosong Sun, Xuanjing Huang, Heng Ji, Zhiyuan Liu, and Yang Liu (Eds.). Springer International Publishing, Cham, 194--206.
- Shengjie Sun Dong Yang Hongchun Zhang Yanxu Chen Chao Wei Xiaonan Meng and Yi Hu. 2018. Important Attribute Identification in Knowledge Graph. https://doi.org/10.48550/arXiv.1810.05320 arXiv:1810.05320 [cs]. · DOI
- Haozheng Tian and Morgan White. 2020. A Pipeline of Aspect Detection and Sentiment Analysis for E-Commerce Customer Reviews. In eCOM@SIGIR.
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Cited by
Sorted by citations
A Usage-centric Take on Intent Understanding in E-Commerce
Zhou, W., Li, T., Vougiouklis, P., Steedman, M., & Pan, J. Z. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2024.emnlp-main.14 · Cited by 1
Self-citation
Metadata
- Authors
- Er-Rahmadi, B., Oncevay, A., Ji, Y., & Pan, J. Z.
- Affiliations
- Huawei Technologies R&D UK, Edinburgh, United Kingdom
- The University of Edinburgh, Edinburgh, United Kingdom
- Huawei Technologies R&D UK & The University of Edinburgh, Edinburgh, United Kingdom
- Venue
- Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
- Publisher
- ACM
- Published
- 2023-07-18
- Pages
- 3320-3324
- Cited by
- 1
- References
- 2
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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