{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T18:34:48Z","timestamp":1743100488309,"version":"3.40.3"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031623615"},{"type":"electronic","value":"9783031623622"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-62362-2_13","type":"book-chapter","created":{"date-parts":[[2024,6,15]],"date-time":"2024-06-15T18:01:48Z","timestamp":1718474508000},"page":"178-196","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["EdgER: Entity Resolution at\u00a0the\u00a0Edge for\u00a0Next Generation Web Systems"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9751-9367","authenticated-orcid":false,"given":"Cristian","family":"Martella","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1082-7293","authenticated-orcid":false,"given":"Angelo","family":"Martella","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6902-0160","authenticated-orcid":false,"given":"Antonella","family":"Longo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,16]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1007\/978-3-030-93975-5_24","volume-title":"Designing Data Spaces","author":"U Ahle","year":"2022","unstructured":"Ahle, U., Hierro, J.J.: FIWARE for data spaces. In: Otto, B., ten Hompel, M., Wrobel, S. (eds.) Designing Data Spaces, pp. 395\u2013417. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-93975-5_24"},{"key":"13_CR2","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1109\/TKDE.2016.2623607","volume":"29","author":"H Altwaijry","year":"2017","unstructured":"Altwaijry, H., Kalashnikov, D.V., Mehrotra, S.: QDA: a query-driven approach to entity resolution. IEEE Trans. Knowl. Data Eng. 29, 402\u2013417 (2017). https:\/\/doi.org\/10.1109\/TKDE.2016.2623607","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"13_CR3","doi-asserted-by":"publisher","first-page":"120","DOI":"10.14778\/2850583.2850587","volume":"9","author":"H Altwaijry","year":"2015","unstructured":"Altwaijry, H., Mehrotra, S., Kalashnikov, D.V.: Query. Proc. VLDB Endowment 9, 120\u2013131 (2015). https:\/\/doi.org\/10.14778\/2850583.2850587","journal-title":"Proc. VLDB Endowment"},{"key":"13_CR4","doi-asserted-by":"publisher","first-page":"108148","DOI":"10.1016\/j.patcog.2021.108148","volume":"120","author":"K Bandara","year":"2021","unstructured":"Bandara, K., Hewamalage, H., Liu, Y.H., et al.: Improving the accuracy of global forecasting models using time series data augmentation. Pattern Recogn. 120, 108148 (2021). https:\/\/doi.org\/10.1016\/j.patcog.2021.108148","journal-title":"Pattern Recogn."},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Brecko, A., Kajati, E., Koziorek, J., Zolotov\u00e1, I.: Federated learning for edge computing: a survey. Appl. Sci. (2022). https:\/\/api.semanticscholar.org\/CorpusID:252258593","DOI":"10.3390\/app12189124"},{"key":"13_CR6","doi-asserted-by":"publisher","unstructured":"Christen, P., Gayler, R., Hawking, D.: Similarity-aware indexing for real-time entity resolution, p.\u00a01565. ACM Press (2009).https:\/\/doi.org\/10.1145\/1645953.1646173","DOI":"10.1145\/1645953.1646173"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Christen, V., Christen, P., Rahm, E.: Informativeness-based active learning for entity resolution. In: PKDD\/ECML Workshops (2019). https:\/\/api.semanticscholar.org\/CorpusID:199521860","DOI":"10.1007\/978-3-030-43887-6_11"},{"key":"13_CR8","doi-asserted-by":"publisher","unstructured":"Christophides, V., et\u00a0al.: An overview of end-to-end entity resolution for big data (2021). https:\/\/doi.org\/10.1145\/3418896","DOI":"10.1145\/3418896"},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1109\/MITP.2022.3224826","volume":"24","author":"J Conde","year":"2022","unstructured":"Conde, J., Munoz-Arcentales, A., Alonso, A., Huecas, G., Salvachua, J.: Collaboration of digital twins through linked open data: architecture with FIWARE as enabling technology. IT Prof. 24, 41\u201346 (2022). https:\/\/doi.org\/10.1109\/MITP.2022.3224826","journal-title":"IT Prof."},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Ferrari, P., et\u00a0al.: Performance evaluation of full-cloud and edge-cloud architectures for industrial IoT anomaly detection based on deep learning. In: 2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4. 0IoT), pp. 420\u2013425. IEEE (2019)","DOI":"10.1109\/METROI4.2019.8792860"},{"issue":"1","key":"13_CR11","doi-asserted-by":"publisher","first-page":"25","DOI":"10.54623\/fue.fcij.6.1.3","volume":"6","author":"MI Gabr","year":"2021","unstructured":"Gabr, M.I., Helmy, Y.M., Elzanfaly, D.S.: Data quality dimensions, metrics, and improvement techniques. Fut. Comput. Inform. J. 6(1), 25\u201344 (2021). https:\/\/doi.org\/10.54623\/fue.fcij.6.1.3","journal-title":"Fut. Comput. Inform. J."},{"issue":"5","key":"13_CR12","doi-asserted-by":"publisher","first-page":"2453","DOI":"10.1007\/s40747-021-00442-6","volume":"7","author":"C Gao","year":"2021","unstructured":"Gao, C., Yang, P., Chen, Y., et al.: An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks. Complex Intell. Syst. 7(5), 2453\u20132468 (2021). https:\/\/doi.org\/10.1007\/s40747-021-00442-6","journal-title":"Complex Intell. Syst."},{"key":"13_CR13","doi-asserted-by":"publisher","first-page":"697","DOI":"10.14778\/2732939.2732943","volume":"7","author":"A Gruenheid","year":"2014","unstructured":"Gruenheid, A., Dong, X.L., Srivastava, D.: Incremental record linkage. Proc. VLDB Endowment 7, 697\u2013708 (2014). https:\/\/doi.org\/10.14778\/2732939.2732943","journal-title":"Proc. VLDB Endowment"},{"key":"13_CR14","unstructured":"Gupta, N., et\u00a0al.: Data quality toolkit: automatic assessment of data quality and remediation for machine learning datasets (2021). arXiv:abs\/2108.05935"},{"key":"13_CR15","unstructured":"Hardy, S., et al.: Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption (2017). arXiv:abs\/1711.10677"},{"issue":"1","key":"13_CR16","doi-asserted-by":"publisher","first-page":"498","DOI":"10.3390\/encyclopedia2010032","volume":"2","author":"MJ Hassenstein","year":"2022","unstructured":"Hassenstein, M.J., Vanella, P.: Data quality-concepts and problems. Encyclopedia 2(1), 498\u2013510 (2022). https:\/\/doi.org\/10.3390\/encyclopedia2010032","journal-title":"Encyclopedia"},{"key":"13_CR17","unstructured":"Hummel, P., Braun, M., Augsberg, S., Dabrock, P.: Sovereignty and data sharing (2018). https:\/\/api.semanticscholar.org\/CorpusID:174780972"},{"issue":"1","key":"13_CR18","doi-asserted-by":"publisher","first-page":"205395172098201","DOI":"10.1177\/2053951720982012","volume":"8","author":"P Hummel","year":"2021","unstructured":"Hummel, P., Braun, M., Tretter, M., Dabrock, P.: Data sovereignty: a review. Big Data Soc. 8(1), 205395172098201 (2021). https:\/\/doi.org\/10.1177\/2053951720982012","journal-title":"Big Data Soc."},{"key":"13_CR19","doi-asserted-by":"publisher","first-page":"7157","DOI":"10.1109\/ACCESS.2023.3237554","volume":"11","author":"J Jithish","year":"2023","unstructured":"Jithish, J., Alangot, B., Mahalingam, N., Yeo, K.S.: Distributed anomaly detection in smart grids: a federated learning-based approach. IEEE Access 11, 7157\u20137179 (2023)","journal-title":"IEEE Access"},{"key":"13_CR20","unstructured":"Kellogg, G., Champin, P.A., Longley, D.: JSON-LD 1.1 - a JSON-based serialization for linked data (2019). https:\/\/api.semanticscholar.org\/CorpusID:202784811"},{"key":"13_CR21","doi-asserted-by":"publisher","unstructured":"Kim, S., et\u00a0al.: Collaborative anomaly detection for internet of things based on federated learning. In: 2020 IEEE\/CIC International Conference on Communications in China (ICCC). IEEE (2020). https:\/\/doi.org\/10.1109\/iccc49849.2020.9238913","DOI":"10.1109\/iccc49849.2020.9238913"},{"issue":"4","key":"13_CR22","doi-asserted-by":"publisher","first-page":"3632","DOI":"10.1109\/tkde.2021.3130234","volume":"35","author":"Y Li","year":"2023","unstructured":"Li, Y., Peng, X., Zhang, J., et al.: DCT-GAN: dilated convolutional transformer-based GAN for time series anomaly detection. IEEE Trans. Knowl. Data Eng. 35(4), 3632\u20133644 (2023). https:\/\/doi.org\/10.1109\/tkde.2021.3130234","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"13_CR23","doi-asserted-by":"publisher","unstructured":"Li, Z., et\u00a0al.: TSA-GAN: a robust generative adversarial networks for time series augmentation. In: 2021 International Joint Conference on Neural Networks (IJCNN). IEEE (2021). https:\/\/doi.org\/10.1109\/ijcnn52387.2021.9534001","DOI":"10.1109\/ijcnn52387.2021.9534001"},{"key":"13_CR24","doi-asserted-by":"publisher","unstructured":"Lovisari, E., J\u00f6nsson, U.T.: A Nyquist criterion for synchronization in networks of heterogeneous linear systems. IFAC Proc. Volumes (IFAC-PapersOnline) 43, 103\u2013108 (2010). https:\/\/doi.org\/10.3182\/20100913-2-FR-4014.00015","DOI":"10.3182\/20100913-2-FR-4014.00015"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Luboshnikov, E., Makarov, I.: Federated learning in named entity recognition. Recent Trends Anal. Images, Soc. Netw. Texts 1357, 90\u2013101 (2021). https:\/\/api.semanticscholar.org\/CorpusID:232336335","DOI":"10.1007\/978-3-030-71214-3_8"},{"key":"13_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/s12243-023-01009-x","author":"JJ L\u00f3pez Escobar","year":"2024","unstructured":"L\u00f3pez Escobar, J.J., D\u00edaz-Redondo, R.P., Gil-Casti\u00f1eira, F.: Unleashing the power of decentralized serverless IoT dataflow architecture for the cloud-to-edge continuum: a performance comparison. Ann. Telecommun. (2024). https:\/\/doi.org\/10.1007\/s12243-023-01009-x","journal-title":"Ann. Telecommun."},{"key":"13_CR27","unstructured":"Martella, C., Longo, A., Zappatore, M., Ficarella, A.: Dataspaces in urban digital twins: a case study in the photovoltaics, vol.\u00a03478 (2023). http:\/\/ceur-ws.org"},{"key":"13_CR28","unstructured":"Mota, M.S., Pantoja, F.L., dos Reis, J.C., Santanch\u00e8, A.: Progressive data integration and semantic enrichment based on LinkedScales and trails. In: Workshop on Semantic Web Applications and Tools for Life Sciences (2016). https:\/\/api.semanticscholar.org\/CorpusID:18522320"},{"key":"13_CR29","doi-asserted-by":"publisher","unstructured":"Nisansala, S., Chandrasiri, G.L., Prasadika, S., Jayasinghe, U.: Microservice based edge computing architecture for internet of things. In: 2022 2nd International Conference on Advanced Research in Computing (ICARC). IEEE (2022). https:\/\/doi.org\/10.1109\/icarc54489.2022.9753930","DOI":"10.1109\/icarc54489.2022.9753930"},{"key":"13_CR30","unstructured":"Nock, R., et al.: Entity resolution and federated learning get a federated resolution (2018). arXiv:abs\/1803.04035"},{"key":"13_CR31","doi-asserted-by":"publisher","unstructured":"Qin, Y., Matsutani, H., Kondo, M.: A selective model aggregation approach in federated learning for online anomaly detection. In: 2020 IEEE iThings and IEEE GreenCom. IEEE (2020). https:\/\/doi.org\/10.1109\/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00119","DOI":"10.1109\/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00119"},{"key":"13_CR32","doi-asserted-by":"publisher","unstructured":"Ramadan, B., Christen, P., Liang, H., Gayler, R.W., Hawking, D.: Dynamic similarity-aware inverted indexing for real-time entity resolution (2013). https:\/\/doi.org\/10.1007\/978-3-642-40319-4_5","DOI":"10.1007\/978-3-642-40319-4_5"},{"key":"13_CR33","doi-asserted-by":"publisher","unstructured":"Risso, F.: Creating an edge-to-cloud computing continuum: status and perspective. In: 2022 3rd International Conference on Embedded & Distributed Systems (EDiS). IEEE (2022). https:\/\/doi.org\/10.1109\/edis57230.2022.9996495","DOI":"10.1109\/edis57230.2022.9996495"},{"issue":"9","key":"13_CR34","doi-asserted-by":"publisher","first-page":"1779","DOI":"10.14778\/3538598.3538602","volume":"15","author":"S Schmidl","year":"2022","unstructured":"Schmidl, S., Wenig, P., Papenbrock, T.: Anomaly detection in time series: a comprehensive evaluation. Proc. VLDB Endowment 15(9), 1779\u20131797 (2022). https:\/\/doi.org\/10.14778\/3538598.3538602","journal-title":"Proc. VLDB Endowment"},{"key":"13_CR35","doi-asserted-by":"publisher","unstructured":"Shadija, D., Rezai, M., Hill, R.: Towards an understanding of microservices. In: 2017 23rd International Conference on Automation and Computing (ICAC). IEEE (2017). https:\/\/doi.org\/10.23919\/iconac.2017.8082018","DOI":"10.23919\/iconac.2017.8082018"},{"key":"13_CR36","doi-asserted-by":"publisher","first-page":"1506","DOI":"10.14778\/3523210.3523226","volume":"15","author":"G Simonini","year":"2022","unstructured":"Simonini, G., Zecchini, L., Bergamaschi, S., Naumann, F.: Entity resolution on-demand. Proc. VLDB Endowment 15, 1506\u20131518 (2022). https:\/\/doi.org\/10.14778\/3523210.3523226","journal-title":"Proc. VLDB Endowment"},{"key":"13_CR37","doi-asserted-by":"publisher","unstructured":"Somma, A., Benedictis, A.D., Zappatore, M., Martella, C., Martella, A., Longo, A.: Digital twin space: the integration of digital twins and data spaces, pp. 4017\u20134025. IEEE (2023). https:\/\/doi.org\/10.1109\/BigData59044.2023.10386737","DOI":"10.1109\/BigData59044.2023.10386737"},{"key":"13_CR38","doi-asserted-by":"publisher","unstructured":"Song, Y., et\u00a0al.: A robust and accurate multivariate time series anomaly detection in fluctuating cloud-edge computing systems. In: 2022 IEEE 24th International Conference on HPCC. IEEE (2022). https:\/\/doi.org\/10.1109\/hpcc-dss-smartcity-dependsys57074.2022.00077","DOI":"10.1109\/hpcc-dss-smartcity-dependsys57074.2022.00077"},{"issue":"5","key":"13_CR39","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1109\/mnet.001.2200235","volume":"36","author":"F Wang","year":"2022","unstructured":"Wang, F., Li, B., Li, B.: Quality-oriented federated learning on the fly. IEEE Netw. 36(5), 152\u2013159 (2022). https:\/\/doi.org\/10.1109\/mnet.001.2200235","journal-title":"IEEE Netw."},{"issue":"1","key":"13_CR40","doi-asserted-by":"publisher","first-page":"100008","DOI":"10.1016\/j.hcc.2021.100008","volume":"1","author":"Q Xia","year":"2021","unstructured":"Xia, Q., Ye, W., Tao, Z., et al.: A survey of federated learning for edge computing: research problems and solutions. High-Confidence Comput. 1(1), 100008 (2021). https:\/\/doi.org\/10.1016\/j.hcc.2021.100008","journal-title":"High-Confidence Comput."},{"key":"13_CR41","doi-asserted-by":"publisher","unstructured":"Zhang, J., et\u00a0al.: Next generation federated learning for edge devices: an overview. In: 2022 IEEE 8th International Conference on Collaboration and Internet Computing (CIC). IEEE (2022). https:\/\/doi.org\/10.1109\/cic56439.2022.00012","DOI":"10.1109\/cic56439.2022.00012"},{"key":"13_CR42","unstructured":"Zhang, X., et al.: Cross-dataset time series anomaly detection for cloud systems. In: 2019 USENIX Annual Technical Conference (USENIX ATC 19), pp. 1063\u20131076 (2019)"}],"container-title":["Lecture Notes in Computer Science","Web Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-62362-2_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,15]],"date-time":"2024-06-15T18:04:08Z","timestamp":1718474648000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-62362-2_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031623615","9783031623622"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-62362-2_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"16 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICWE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tampere","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Finland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icwe2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icwe2024.webengineering.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}