{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,24]],"date-time":"2025-08-24T01:55:57Z","timestamp":1756000557755,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030888848"},{"type":"electronic","value":"9783030888855"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-88885-5_7","type":"book-chapter","created":{"date-parts":[[2021,10,13]],"date-time":"2021-10-13T17:25:06Z","timestamp":1634145906000},"page":"91-107","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Mining Interpretable Spatio-Temporal Logic Properties for Spatially Distributed Systems"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4986-5553","authenticated-orcid":false,"given":"Sara","family":"Mohammadinejad","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4683-5540","authenticated-orcid":false,"given":"Jyotirmoy V.","family":"Deshmukh","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2263-9342","authenticated-orcid":false,"given":"Laura","family":"Nenzi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,12]]},"reference":[{"key":"7_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1007\/978-3-642-29860-8_12","volume-title":"Runtime Verification","author":"E Asarin","year":"2012","unstructured":"Asarin, E., Donz\u00e9, A., Maler, O., Nickovic, D.: Parametric identification of temporal properties. In: Khurshid, S., Sen, K. (eds.) RV 2011. LNCS, vol. 7186, pp. 147\u2013160. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-29860-8_12"},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Bartocci, E., Bortolussi, L., Loreti, M., Nenzi, L.: Monitoring mobile and spatially distributed cyber-physical systems. In: Proceedings of MEMOCODE (2017)","DOI":"10.1145\/3127041.3127050"},{"key":"7_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1007\/978-3-030-60508-7_23","volume-title":"Runtime Verification","author":"E Bartocci","year":"2020","unstructured":"Bartocci, E., Bortolussi, L., Loreti, M., Nenzi, L., Silvetti, S.: MoonLight: a lightweight tool for monitoring spatio-temporal properties. In: Deshmukh, J., Ni\u010dkovi\u0107, D. (eds.) RV 2020. LNCS, vol. 12399, pp. 417\u2013428. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-60508-7_23"},{"key":"7_CR4","unstructured":"Cobo, G., Garc\u00eda-Sol\u00f3rzano, D., Santamar\u00eda, E., Mor\u00e1n, J.A., Melench\u00f3n, J., Monzo, C.: Modeling students\u2019 activity in online discussion forums: a strategy based on time series and agglomerative hierarchical clustering. In: Educational Data Mining (2010)"},{"issue":"1","key":"7_CR5","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/BF01890115","volume":"1","author":"WH Day","year":"1984","unstructured":"Day, W.H., Edelsbrunner, H.: Efficient algorithms for agglomerative hierarchical clustering methods. J. Classif. 1(1), 7\u201324 (1984)","journal-title":"J. Classif."},{"key":"7_CR6","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/978-3-662-05281-5_2","volume-title":"Trends in Nonlinear Analysis","author":"B Fiedler","year":"2003","unstructured":"Fiedler, B., Scheel, A.: Spatio-temporal dynamics of reaction-diffusion patterns. In: Kirkilionis, M., Kr\u00f6mker, S., Rannacher, R., Tomi, F. (eds.) Trends in Nonlinear Analysis, pp. 23\u2013152. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-3-662-05281-5_2"},{"key":"7_CR7","first-page":"1","volume":"367","author":"X Huang","year":"2016","unstructured":"Huang, X., Ye, Y., Xiong, L., Lau, R.Y., Jiang, N., Wang, S.: Time series k-means: a new k-means type smooth subspace clustering for time series data. Inf. Sci. 367, 1\u201313 (2016)","journal-title":"Inf. Sci."},{"issue":"11","key":"7_CR8","doi-asserted-by":"publisher","first-page":"1704","DOI":"10.1109\/TCAD.2015.2421907","volume":"34","author":"X Jin","year":"2015","unstructured":"Jin, X., Donz\u00e9, A., Deshmukh, J.V., Seshia, S.A.: Mining requirements from closed-loop control models. IEEE Trans. CAD 34(11), 1704\u20131717 (2015)","journal-title":"IEEE Trans. CAD"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Kiamari, M., Ramachandran, G., Nguyen, Q., Pereira, E., Holm, J., Krishnamachari, B.: Covid-19 risk estimation using a time-varying sir-model. In: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Modeling and Understanding the Spread of COVID-19, pp. 36\u201342 (2020)","DOI":"10.1145\/3423459.3430759"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Kreikemeyer, J.N., Hillston, J., Uhrmacher, A.: Probing the performance of the Edinburgh bike sharing system using SSTL. In: Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, pp. 141\u2013152 (2020)","DOI":"10.1145\/3384441.3395990"},{"key":"7_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/978-3-319-63387-9_15","volume-title":"Computer Aided Verification","author":"M Vazquez-Chanlatte","year":"2017","unstructured":"Vazquez-Chanlatte, M., Deshmukh, J.V., Jin, X., Seshia, S.A.: Logical clustering and learning for time-series data. In: Majumdar, R., Kun\u010dak, V. (eds.) CAV 2017. LNCS, vol. 10426, pp. 305\u2013325. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-63387-9_15"},{"key":"7_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1007\/978-3-540-30206-3_12","volume-title":"Formal Techniques, Modelling and Analysis of Timed and Fault-Tolerant Systems","author":"O Maler","year":"2004","unstructured":"Maler, O., Nickovic, D.: Monitoring temporal properties of continuous signals. In: Lakhnech, Y., Yovine, S. (eds.) FORMATS\/FTRTFT -2004. LNCS, vol. 3253, pp. 152\u2013166. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-30206-3_12"},{"key":"7_CR13","volume-title":"Machine Learning","author":"TM Mitchell","year":"1997","unstructured":"Mitchell, T.M.: Machine Learning, 1st edn. McGraw-Hill Inc., New York (1997)","edition":"1"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Mohammadinejad, S., Deshmukh, J.V., Puranic, A.G.: Mining environment assumptions for cyber-physical system models. In: Proceedings of ICCPS (2020)","DOI":"10.1109\/ICCPS48487.2020.00016"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Mohammadinejad, S., Deshmukh, J.V., Puranic, A.G., Vazquez-Chanlatte, M., Donz\u00e9, A.: Interpretable classification of time-series data using efficient enumerative techniques. In: Proceedings of HSCC (2020)","DOI":"10.1145\/3365365.3382218"},{"key":"7_CR16","unstructured":"Nenzi, L., Bortolussi, L., Ciancia, V., Loreti, M., Massink, M.: Qualitative and quantitative monitoring of spatio-temporal properties with SSTL. LMCS 14(4) (2018)"},{"key":"7_CR17","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53\u201365 (1987)","journal-title":"J. Comput. Appl. Math."},{"key":"7_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1007\/978-3-030-03769-7_22","volume-title":"Runtime Verification","author":"M Vazquez-Chanlatte","year":"2018","unstructured":"Vazquez-Chanlatte, M., Ghosh, S., Deshmukh, J.V., Sangiovanni-Vincentelli, A., Seshia, S.A.: Time-series learning using monotonic logical properties. In: Colombo, C., Leucker, M. (eds.) RV 2018. LNCS, vol. 11237, pp. 389\u2013405. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-03769-7_22"},{"key":"7_CR19","doi-asserted-by":"crossref","unstructured":"Zakaria, J., Mueen, A., Keogh, E.: Clustering time series using unsupervised-shapelets. In: 2012 IEEE 12th International Conference on Data Mining, pp. 785\u2013794. IEEE (2012)","DOI":"10.1109\/ICDM.2012.26"}],"container-title":["Lecture Notes in Computer Science","Automated Technology for Verification and Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-88885-5_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,13]],"date-time":"2021-10-13T17:55:27Z","timestamp":1634147727000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-88885-5_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030888848","9783030888855"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-88885-5_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"12 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ATVA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Automated Technology for Verification and Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gold Coast, QLD","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"atva2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/formal-analysis.com\/atva\/2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"75","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"25% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"In addition there are 4 tool papers. The conference was held online because of the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}