1 |
闫蓉,高光来. 基于检索结果排序的伪相关反馈[J]. 计算机应用, 2016, 36(8): 2099-2102, 2143. 10.11772/j.issn.1001-9081.2016.08.2099
|
|
YAN R, GAO G L. Pseudo relevance feedback based on sorted retrieval result[J]. Journal of Computer Applications, 2016, 36(8): 2099-2102, 2143. 10.11772/j.issn.1001-9081.2016.08.2099
|
2 |
闫蓉,高光来. 基于伪文档的伪相关反馈方法[J]. 中文信息学报, 2016, 30(6): 156-163, 172. 10.11772/j.issn.1001-9081.2016.08.2099
|
|
YAN R, GAO G L. A new pseudo relevance feedback based on pseudo document[J]. Journal of Chinese Information Processing, 2016, 30(6): 156-163, 172. 10.11772/j.issn.1001-9081.2016.08.2099
|
3 |
ROCCHIO J. Relevance feedback in information retrieval[M]// SALTON G. The SMART Retrieval System: Experiments in Automatic Document Processing. Upper Saddle River, NJ: Prentice Hall, 1971: 313-323.
|
4 |
ABDUL-JALEEL N, ALLAN J, CROFT W B, et al. UMass at TREC 2004: novelty and HARD[C/OL]// Proceedings of the 13th Text REtrieval Conference [2022-02-11].. 10.21236/ada460118
|
5 |
ZHAI C X, LAFFERTY J. Model-based feedback in the language modeling approach to information retrieval[C]// Proceedings of the 10th ACM International Conference on Information and Knowledge Management. New York: ACM, 2001: 403-410. 10.1145/502585.502654
|
6 |
AMATI G, C J van RIJSBERGEN. Probabilistic models of information retrieval based on measuring the divergence from randomness[J]. ACM Transactions on Information Systems, 2002, 20(4): 357-389. 10.1145/582415.582416
|
7 |
DIAZ F, MITRA B, CRASWELL N. Query expansion with locally-trained word embeddings[C]// Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: ACL, 2016: 367-377. 10.18653/v1/p16-1035
|
8 |
ROY D, GANGULY D, BHATIA S, et al. Using word embeddings for information retrieval: how collection and term normalization choices affect performance[C]// Proceedings of the 27th ACM International Conference on Information and Knowledge Management. New York: ACM, 2018: 1835-1838. 10.1145/3269206.3269277
|
9 |
黄名选. 关联模式挖掘与词向量学习融合的伪相关反馈查询扩展[J]. 电子学报, 2021, 49(7): 1305-1313. 10.12263/DZXB.20200654
|
|
HUANG M X. Pseudo-relevance feedback query expansion based on the fusion of association pattern mining and word embedding learning[J]. Acta Electronica Sinica, 2021, 49(7): 1305-1313. 10.12263/DZXB.20200654
|
10 |
DEVLIN J, CHANG M W, LEE K, et al. BERT: pre-training of deep bidirectional transformers for language understanding[C]// 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). Stroudsburg, PA: ACL, 2019: 4171-4186. 10.18653/v1/n18-2
|
11 |
LIN J, NOGUEIRA R, YATES A. Pretrained transformers for text ranking: BERT and beyond[J]. Synthesis Lectures on Human Language Technologies, 2021, 14(4): 18-20. 10.2200/s01123ed1v01y202108hlt053
|
12 |
YU H C, XIONG C Y, CALLAN J. Improving query representations for dense retrieval with pseudo relevance feedback[C]// Proceedings of the 30th ACM International Conference on Information and Knowledge Management. New York: ACM, 2021: 3592-3596. 10.1145/3459637.3482124
|
13 |
XIONG L, XIONG C Y, LI Y, et al. Approximate nearest neighbor negative contrastive learning for dense text retrieval[EB/OL]. (2023-01-24) [2023-02-12]..
|
14 |
WANG X, MACDONALD C, TONELLOTTO N, et al. Pseudo-relevance feedback for multiple representation dense retrieval[C]// Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval. New York: ACM, 2021: 297-306. 10.1145/3471158.3472250
|
15 |
KHATTAB O, ZAHARIA M. ColBERT: efficient and effective passage search via contextualized late interaction over BERT[C]// Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2020: 39-48. 10.1145/3397271.3401075
|
16 |
QIU X P, SUN T X, XU Y G, et al. Pre-trained models for natural language processing: a survey[J]. Science China Technological Sciences, 2020, 63(10): 1872-1897. 10.1007/s11431-020-1647-3
|
17 |
NOGUEIRA R, CHO K. Passage re-ranking with BERT[EB/OL]. (2020-04-14) [2022-03-12]..
|
18 |
ROBERTSON S E, WALKER S, BEAULIEU M M, et al. Okapi at TREC-4[C/OL]// Proceedings of the 4th Text REtrieval Conference [2022-03-11] . 10.1108/eum0000000007188
|
19 |
AKKALYONCU YILMAZ Z, YANG W, ZHANG H T, et al. Cross-domain modeling of sentence-level evidence for document retrieval[C]// Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Stroudsburg, PA: ACL, 2019: 3490-3496. 10.18653/v1/d19-1352
|
20 |
MacAVANEY S, YATES A, COHAN A, et al. CEDR: contextualized embeddings for document ranking[C]// Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2019: 1101-1104. 10.1145/3331184.3331317
|
21 |
LI C J, YATES A, MacAVANEY S, et al. PARADE: passage representation aggregation for document reranking[EB/OL]. (2021-07-10) [2022-03-12]..
|
22 |
KARPUKHIN V, OGUZ B, MIN S, et al. Dense passage retrieval for open-domain question answering[C]// Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: ACL, 2020: 6769-6781. 10.18653/v1/2020.emnlp-main.550
|
23 |
ZHAN J T, MAO J X, LIU Y Q, et al. RepBERT: contextualized text embeddings for first-stage retrieval[EB/OL]. (2020-07-20) [2022-03-12]..
|
24 |
DAI Z, CALLAN J. Context-aware document term weighting for ad-hoc search[C]// Proceedings of The Web Conference 2020. New York: ACM, 2020: 1897-1907. 10.1145/3366423.3380258
|
25 |
NOGUEIRA R, YANG W, LIN J, et al. Document expansion by query prediction[EB/OL]. (2019-09-25) [2022-03-12]..
|
26 |
NOGUEIRA R, LIN J, EPISTEMIC A I. From doc2query to docTTTTTquery[EB/OL]. [2022-03-12]..
|
27 |
LI C J, SUN Y F, HE B, et al. NPRF: a neural pseudo relevance feedback framework for ad-hoc information retrieval[C]// Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: ACL, 2018: 4482-4491. 10.18653/v1/d18-1478
|
28 |
ZHENG Z, HUI K, HE B, et al. BERT-QE: contextualized query expansion for document re-ranking[C]// Findings of the Association for Computational Linguistics: EMNLP 2020. Stroudsburg, PA: ACL, 2020: 4718-4728. 10.18653/v1/2020.findings-emnlp.424
|
29 |
VOORHEES E M. Overview of the TREC 2004 Robust Track. [C]// Proceedings of the 13th Text REetrieval Conference: TREC 2004. Gaithersburg, Maryland: National Institute of Standards and Technology, 2004: 52-69. 10.6028/nist.sp.500-261
|
30 |
HAWKING D, VOORHEES E, CRASWELL N, et al. Overview of the TREC-8 Web track[C]// Proceedings of the 8th Text Retrieval Conference: TREC 1999. Gaithersburg, Maryland: National Institute of Standards and Technology, 1999: 131-150. 10.6028/nist.sp.500-242
|
31 |
YANG P L, FANG H, LIN J. Anserini: enabling the use of Lucene for information retrieval research[C]// Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2017: 1253-1256. 10.1145/3077136.3080721
|