{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T03:46:42Z","timestamp":1769140002585,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":36,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557158","type":"print"},{"value":"9789819557165","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5716-5_31","type":"book-chapter","created":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T13:06:51Z","timestamp":1769087211000},"page":"502-516","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LSTM-Based Query Performance Optimization in\u00a0LSM-Trees"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0664-4954","authenticated-orcid":false,"given":"Yuxin","family":"Guo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6478-1226","authenticated-orcid":false,"given":"Shuhe","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1191-1673","authenticated-orcid":false,"given":"Hongjuan","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1077-1322","authenticated-orcid":false,"given":"Hui","family":"Kang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,23]]},"reference":[{"key":"31_CR1","doi-asserted-by":"crossref","unstructured":"Al-Selwi, S.M., et al.: RNN-LSTM: From applications to modeling techniques and beyond\u2014systematic review. J. King Saud Univ.-Comput. Inf. Sci. p. 102068 (2024)","DOI":"10.1016\/j.jksuci.2024.102068"},{"key":"31_CR2","doi-asserted-by":"crossref","unstructured":"Cai, M., Jiang, X., Shen, J., Ye, B.: Splitdb: Closing the performance gap for LSM-tree-based key-value stores. IEEE Trans. Comput. (2023)","DOI":"10.1109\/TC.2023.3326982"},{"issue":"1","key":"31_CR3","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/TC.2023.3326982","volume":"73","author":"M Cai","year":"2024","unstructured":"Cai, M., Jiang, X., Shen, J., Ye, B.: Splitdb: Closing the performance gap for LSM-tree-based key-value stores. IEEE Trans. Computers 73(1), 206\u2013220 (2024)","journal-title":"IEEE Trans. Computers"},{"issue":"2","key":"31_CR4","first-page":"381","volume":"19","author":"KW Cowdrey","year":"2018","unstructured":"Cowdrey, K.W., de Lange, J., Malekian, R., Wanneburg, J., Jose, A.C.: Applying queueing theory for the optimization of a banking model. J. Internet Technol. 19(2), 381\u2013389 (2018)","journal-title":"J. Internet Technol."},{"key":"31_CR5","unstructured":"Dai, Y., et al.: From Wisckey to bourbon: A learned index for log-structured merge trees. In: 14th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2020, Virtual Event, November 4-6, 2020, pp. 155\u2013171. USENIX Association (2020)"},{"key":"31_CR6","unstructured":"Dai, Z., Shrivastava, A.: Adaptive learned bloom filter (ADA-BF): Efficient utilization of the classifier. arXiv preprint arXiv:1910.09131 (2019)"},{"issue":"4","key":"31_CR7","doi-asserted-by":"publisher","first-page":"600","DOI":"10.14778\/3436905.3436919","volume":"14","author":"K Deeds","year":"2020","unstructured":"Deeds, K., Hentschel, B., Idreos, S.: Stacked filters: Learning to filter by structure. Proc. VLDB Endow. 14(4), 600\u2013612 (2020)","journal-title":"Proc. VLDB Endow."},{"issue":"8","key":"31_CR8","doi-asserted-by":"publisher","first-page":"1162","DOI":"10.14778\/3389133.3389135","volume":"13","author":"P Ferragina","year":"2020","unstructured":"Ferragina, P., Vinciguerra, G.: THE PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds. Proc. VLDB Endow. 13(8), 1162\u20131175 (2020)","journal-title":"Proc. VLDB Endow."},{"key":"31_CR9","doi-asserted-by":"crossref","unstructured":"He, K., An, Y., Luo, Y., Liu, X., Wang, G.: Flatlsm: Write-optimized LSM-tree for pm-based KV stores. ACM Trans. Storage 19(2), 19:1\u201319:26 (2023)","DOI":"10.1145\/3579855"},{"key":"31_CR10","doi-asserted-by":"crossref","unstructured":"Huang, D., et al.: Splitzns: Towards an efficient LSM-tree on zoned namespace SSDS. ACM Trans. Archit. Code Optim. 20(3), 45:1\u201345:26 (2023)","DOI":"10.1145\/3608476"},{"key":"31_CR11","doi-asserted-by":"crossref","unstructured":"Huang, K., Jia, Z., Shen, Z., Shao, Z., Chen, F.: Less is more: De-amplifying I\/OS for key-value stores with a log-assisted LSM-tree. In: 37th IEEE International Conference on Data Engineering, ICDE 2021, Chania, Greece, April 19-22, 2021, pp. 612\u2013623. IEEE (2021)","DOI":"10.1109\/ICDE51399.2021.00059"},{"issue":"17","key":"31_CR12","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.5186","volume":"31","author":"E Jafarnejad Ghomi","year":"2019","unstructured":"Jafarnejad Ghomi, E., Rahmani, A.M., Qader, N.N.: Applying queue theory for modeling of cloud computing: A systematic review. Concurr. Comput. Prac. Exp. 31(17), e5186 (2019)","journal-title":"Concurr. Comput. Prac. Exp."},{"key":"31_CR13","doi-asserted-by":"crossref","unstructured":"Kim, D., Lee, J., Lim, K.S., Heo, J., Ham, T.J., Lee, J.W.: An LSM tree augmented with b$$ ^{\\text{+}}$$ tree on nonvolatile memory. ACM Trans. Storage 20(1), 4:1\u20134:24 (2024)","DOI":"10.1145\/3633475"},{"key":"31_CR14","doi-asserted-by":"crossref","unstructured":"Kipf, A., et al.: Radixspline: a single-pass learned index. In: Bordawekar, R., Shmueli, O., Tatbul, N., Ho, T.K. (eds.) Proceedings of the Third International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM@SIGMOD 2020, Portland, Oregon, USA, June 19, 2020, pp. 5:1\u20135:5. ACM (2020)","DOI":"10.1145\/3401071.3401659"},{"issue":"3","key":"31_CR15","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1007\/s00778-022-00755-z","volume":"32","author":"M Li","year":"2023","unstructured":"Li, M., et al.: A pareto optimal bloom filter family with hash adaptivity. VLDB J. 32(3), 525\u2013548 (2023)","journal-title":"VLDB J."},{"key":"31_CR16","unstructured":"Li, Y., Tian, C., Guo, F., Li, C., Xu, Y.: Elasticbf: Elastic bloom filter with hotness awareness for boosting read performance in large key-value stores. In: Malkhi, D., Tsafrir, D. (eds.) Proceedings of the 2019 USENIX Annual Technical Conference, USENIX ATC 2019, Renton, WA, USA, July 10-12, 2019, pp. 739\u2013752. USENIX Association (2019)"},{"key":"31_CR17","doi-asserted-by":"crossref","unstructured":"Lu, L., Pillai, T.S., Gopalakrishnan, H., Arpaci-Dusseau, A.C., Arpaci-Dusseau, R.H.: Wisckey: Separating keys from values in ssd-conscious storage. ACM Trans. Storage 13(1), 5:1\u20135:28 (2017)","DOI":"10.1145\/3033273"},{"key":"31_CR18","doi-asserted-by":"crossref","unstructured":"Luo, Z., et al.: Moonkv: Optimizing update-intensive workloads for nvm-based key-value stores. In: Chen, G., Khan, L., Gao, X., Qiu, M., Pedrycz, W., Wu, X. (eds.) IEEE International Conference on Data Mining, ICDM 2023, Shanghai, China, December 1-4, 2023, pp. 478\u2013487. IEEE (2023)","DOI":"10.1109\/ICDM58522.2023.00057"},{"key":"31_CR19","doi-asserted-by":"crossref","unstructured":"Ma, L., Aken, D.V., Hefny, A., Mezerhane, G., Pavlo, A., Gordon, G.J.: Query-based workload forecasting for self-driving database management systems. In: Das, G., Jermaine, C.M., Bernstein, P.A. (eds.) Proceedings of the 2018 International Conference on Management of Data, SIGMOD Conference 2018, Houston, TX, USA, June 10-15, 2018, pp. 631\u2013645. ACM (2018)","DOI":"10.1145\/3183713.3196908"},{"issue":"12","key":"31_CR20","doi-asserted-by":"publisher","first-page":"3217","DOI":"10.14778\/3415478.3415546","volume":"13","author":"Y Matsunobu","year":"2020","unstructured":"Matsunobu, Y., Dong, S., Lee, H.: Myrocks: LSM-tree database storage engine serving Facebook\u2019s social graph. Proc. VLDB Endowment 13(12), 3217\u20133230 (2020)","journal-title":"Proc. VLDB Endowment"},{"issue":"8","key":"31_CR21","doi-asserted-by":"publisher","first-page":"3867","DOI":"10.1109\/TKDE.2020.3027191","volume":"34","author":"P Menon","year":"2020","unstructured":"Menon, P., Qadah, T.M., Rabl, T., Sadoghi, M., Jacobsen, H.A.: Logstore: A workload-aware, adaptable key-value store on hybrid storage systems. IEEE Trans. Knowl. Data Eng. 34(8), 3867\u20133882 (2020)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"31_CR22","unstructured":"Ren, Y., Ren, Y., Li, X., Hu, Y., Li, J., Lee, P.P.C.: ELECT: enabling erasure coding tiering for lsm-tree-based storage. In: Ma, X., Won, Y. (eds.) 22nd USENIX Conference on File and Storage Technologies, FAST 2024, Santa Clara, CA, USA, February 27-29, 2024, pp. 293\u2013310. USENIX Association (2024)"},{"key":"31_CR23","doi-asserted-by":"crossref","unstructured":"Sarkar, S., Athanassoulis, M.: Dissecting, designing, and optimizing lsm-based data stores. In: Ives, Z.G., Bonifati, A., Abbadi, A.E. (eds.) SIGMOD \u201922: International Conference on Management of Data, Philadelphia, PA, USA, June 12 - 17, 2022, pp. 2489\u20132497. ACM (2022)","DOI":"10.1145\/3514221.3522563"},{"key":"31_CR24","doi-asserted-by":"crossref","unstructured":"Sarkar, S., Dayan, N., Athanassoulis, M.: The LSM design space and its read optimizations. In: 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023, pp. 3578\u20133584. IEEE (2023)","DOI":"10.1109\/ICDE55515.2023.00273"},{"key":"31_CR25","doi-asserted-by":"crossref","unstructured":"Sarkar, S., Papon, T.I., Staratzis, D., Athanassoulis, M.: Lethe: A tunable delete-aware LSM engine. In: Maier, D., Pottinger, R., Doan, A., Tan, W., Alawini, A., Ngo, H.Q. (eds.) Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020, pp. 893\u2013908. ACM (2020)","DOI":"10.1145\/3318464.3389757"},{"key":"31_CR26","unstructured":"Sato, A., Matsui, Y.: Fast partitioned learned bloom filter. Adv. Neural Inf. Process. Syst. 36 (2024)"},{"key":"31_CR27","doi-asserted-by":"crossref","unstructured":"Selvin, S., Vinayakumar, R., Gopalakrishnan, E.A., Menon, V.K., Soman, K.P.: Stock price prediction using LSTM, RNN and CNN-sliding window model. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1643\u20131647 (2017)","DOI":"10.1109\/ICACCI.2017.8126078"},{"key":"31_CR28","doi-asserted-by":"crossref","unstructured":"Wang, R., Wang, J., Kadam, P., \u00d6zsu, M.T., Aref, W.G.: DLSM: An LSM-based index for memory disaggregation. In: 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023, pp. 2835\u20132849. IEEE (2023)","DOI":"10.1109\/ICDE55515.2023.00217"},{"key":"31_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2021.103077","volume":"186","author":"Q Wu","year":"2021","unstructured":"Wu, Q., Wang, Q., Zhang, M., Zheng, R., Zhu, J., Hu, J.: Learned bloom-filter for the efficient name lookup in information-centric networking. J. Netw. Comput. Appl. 186, 103077 (2021)","journal-title":"J. Netw. Comput. Appl."},{"key":"31_CR30","doi-asserted-by":"crossref","unstructured":"Xie, R., et al.: Hash adaptive bloom filter. In: 37th IEEE International Conference on Data Engineering, ICDE 2021, Chania, Greece, April 19-22, 2021, pp. 636\u2013647. IEEE (2021)","DOI":"10.1109\/ICDE51399.2021.00061"},{"key":"31_CR31","doi-asserted-by":"crossref","unstructured":"Xu, P., et al.: Building a fast and efficient LSM-tree store by integrating local storage with cloud storage. ACM Trans. Archit. Code Optim. 19(3), 37:1\u201337:26 (2022)","DOI":"10.1145\/3527452"},{"issue":"11","key":"31_CR32","doi-asserted-by":"publisher","first-page":"1976","DOI":"10.14778\/3407790.3407803","volume":"13","author":"L Yang","year":"2020","unstructured":"Yang, L., et al.: Leaper: A learned prefetcher for cache invalidation in LSM-tree based storage engines. Proc. VLDB Endow. 13(11), 1976\u20131989 (2020)","journal-title":"Proc. VLDB Endow."},{"key":"31_CR33","unstructured":"Ping Yu, J., Hui Chen, H., Bo\u00a0Qian, J., Hong Dong, Y.: A heterogeneous bloom filter scheme in lsm tree based on hotness prediction. Acta Electronica Sinica 49(11), 2090 (2021)"},{"key":"31_CR34","doi-asserted-by":"crossref","unstructured":"Yu, J., Chen, H., Qian, J., Dong, Y.: LTG-LSM: the optimal structure in LSM-tree combined with reading hotness. In: 26th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2020, Hong Kong, December 2-4, 2020, pp.\u00a01\u20138. IEEE (2020)","DOI":"10.1109\/ICPADS51040.2020.00011"},{"issue":"12","key":"31_CR35","doi-asserted-by":"publisher","first-page":"2183","DOI":"10.14778\/3352063.3352134","volume":"12","author":"J Zhang","year":"2019","unstructured":"Zhang, J., et al.: S3: A scalable in-memory skip-list index for key-value store. Proc. VLDB Endow. 12(12), 2183\u20132194 (2019)","journal-title":"Proc. VLDB Endow."},{"key":"31_CR36","unstructured":"Zhu, Z.: Shamba: Reducing bloom filter overhead in LSM trees. In: Efthymiou, V., Hu, X. (eds.) Proceedings of the VLDB 2023 PhD Workshop co-located with the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28, 2023. CEUR Workshop Proceedings, vol.\u00a03452, pp. 17\u201320. CEUR-WS.org (2023)"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5716-5_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T13:07:01Z","timestamp":1769087221000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5716-5_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557158","9789819557165"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5716-5_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"23 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenyang","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/apweb2025.sau.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}