{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T21:03:26Z","timestamp":1726261406028},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031622687"},{"type":"electronic","value":"9783031622694"}],"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\/978-3-031-62269-4_4","type":"book-chapter","created":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T14:02:22Z","timestamp":1718892142000},"page":"45-60","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Explainability in\u00a0Mobility Data Science Through a\u00a0Combination of\u00a0Methods"],"prefix":"10.1007","author":[{"given":"Georgios","family":"Makridis","sequence":"first","affiliation":[]},{"given":"Vasileios","family":"Koukos","sequence":"additional","affiliation":[]},{"given":"Georgios","family":"Fatouros","sequence":"additional","affiliation":[]},{"given":"Maria Margarita","family":"Separdani","sequence":"additional","affiliation":[]},{"given":"Dimosthenis","family":"Kyriazis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,21]]},"reference":[{"issue":"14","key":"4_CR1","doi-asserted-by":"publisher","first-page":"4738","DOI":"10.3390\/s21144738","volume":"21","author":"A Abdollahi","year":"2021","unstructured":"Abdollahi, A., Pradhan, B.: Urban vegetation mapping from aerial imagery using explainable AI (XAI). Sensors 21(14), 4738 (2021)","journal-title":"Sensors"},{"key":"4_CR2","doi-asserted-by":"publisher","unstructured":"Altieri, M., Ceci, M., Corizzo, R.: Explainable spatio-temporal graph modeling. In: International Conference on Discovery Science, pp. 174\u2013188. Springer (2023). https:\/\/doi.org\/10.1007\/978-3-031-45275-8_12","DOI":"10.1007\/978-3-031-45275-8_12"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Amiri, S.S., Mottahedi, S., Lee, E.R., Hoque, S.: Peeking inside the black-box: explainable machine learning applied to household transportation energy consumption. Comput. Environ. Urban Syst. 88, 101647 (2021)","DOI":"10.1016\/j.compenvurbsys.2021.101647"},{"issue":"1","key":"4_CR4","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1177\/1473871612457601","volume":"12","author":"N Andrienko","year":"2013","unstructured":"Andrienko, N., Andrienko, G.: Visual analytics of movement: an overview of methods, tools and procedures. Inf. Vis. 12(1), 3\u201324 (2013)","journal-title":"Inf. Vis."},{"key":"4_CR5","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Behl, S., Rao, A., Aggarwal, S., Chadha, S., Pannu, HS.: Twitter for disaster relief through sentiment analysis for COVID-19 and natural hazard crises. Int. J. Disaster Risk Reduction, 55, pp. 102101 (2021)","DOI":"10.1016\/j.ijdrr.2021.102101"},{"key":"4_CR7","volume":"14","author":"G Fatouros","year":"2023","unstructured":"Fatouros, G., Soldatos, J., Kouroumali, K., Makridis, G., Kyriazis, D.: Transforming sentiment analysis in the financial domain with ChatGPT. Mach. Learn. Appl. 14, 100508 (2023)","journal-title":"Mach. Learn. Appl."},{"key":"4_CR8","first-page":"1","volume":"60","author":"X Guo","year":"2021","unstructured":"Guo, X., Hou, B., Ren, B., Ren, Z., Jiao, L.: Network pruning for remote sensing images classification based on interpretable CNNS. IEEE Trans. Geosci. Remote Sens. 60, 1\u201315 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"5","key":"4_CR9","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1080\/13658816.2023.2191256","volume":"37","author":"C-Y Hsu","year":"2023","unstructured":"Hsu, C.-Y., Li, W.: Explainable GeoAI: can saliency maps help interpret artificial intelligence\u2019s learning process? An empirical study on natural feature detection. Int. J. Geogr. Inf. Sci. 37(5), 963\u2013987 (2023)","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"4_CR10","unstructured":"Jalali, A., Graser, A., Heistracher, C.: Towards explainable AI for mobility data science. arXiv preprint arXiv:2307.08461 (2023)"},{"key":"4_CR11","unstructured":"Kim, B., Khanna, R., Koyejo, O.O.: Examples are not enough, learn to criticize! criticism for interpretability. Adv. Neural Inf. Process. Syst. 29 (2016)"},{"issue":"1","key":"4_CR12","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1186\/s40537-022-00651-x","volume":"9","author":"D Kotios","year":"2022","unstructured":"Kotios, D., Makridis, G., Fatouros, G., Kyriazis, D.: Deep learning enhancing banking services: a hybrid transaction classification and cash flow prediction approach. J. Big Data 9(1), 100 (2022)","journal-title":"J. Big Data"},{"key":"4_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1007\/3-540-45799-2_10","volume-title":"Geographic Information Science","author":"P Laube","year":"2002","unstructured":"Laube, P., Imfeld, S.: Analyzing Relative Motion within Groups oftrackable moving point objects. In: Egenhofer, M.J., Mark, D.M. (eds.) GIScience 2002. LNCS, vol. 2478, pp. 132\u2013144. Springer, Heidelberg (2002). https:\/\/doi.org\/10.1007\/3-540-45799-2_10"},{"key":"4_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2022.101845","volume":"96","author":"Z Li","year":"2022","unstructured":"Li, Z.: Extracting spatial effects from machine learning model using local interpretation method: an example of SHAP and XGBoost. Comput. Environ. Urban Syst. 96, 101845 (2022)","journal-title":"Comput. Environ. Urban Syst."},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Liu, X., et al.: Predicting skin cancer risk from facial images with an explainable artificial intelligence (XAI) based approach: a proof-of-concept study. medRxiv 71, 2023\u201310 (2023)","DOI":"10.1101\/2023.10.04.23296549"},{"key":"4_CR16","unstructured":"Lundberg, S.M., Lee, S.I.: A unified approach to interpreting model predictions. In: Advance Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"18","key":"4_CR17","doi-asserted-by":"publisher","first-page":"3650","DOI":"10.3390\/rs13183650","volume":"13","author":"R Luo","year":"2021","unstructured":"Luo, R., Xing, J., Chen, L., Pan, Z., Cai, X., Li, Z., Wang, J., Ford, A.: Glassboxing deep learning to enhance aircraft detection from SAR imagery. Remote Sens. 13(18), 3650 (2021)","journal-title":"Remote Sens."},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Makridis, G., Fatouros, G., Koukos, V., Kotios, D., Kyriazis, D., Soldatos, I.: XAI for time-series classification leveraging image highlight methods. arXiv preprint arXiv:2311.17110 (2023)","DOI":"10.1007\/978-3-031-51643-6_28"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Makridis, G., et al.: XAI enhancing cyber defence against adversarial attacks in industrial applications. In: 2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS), pp. 1\u20138. IEEE (2022)","DOI":"10.1109\/IPAS55744.2022.10052858"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: why should i trust you? Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144 (2016)","DOI":"10.1145\/2939672.2939778"},{"key":"4_CR21","unstructured":"Simonyan, k., Vedaldi, A., Zisserman, A.: Deep inside convolutional networks: visualising image classification models and saliency maps. arXiv preprint arXiv:1312.6034 (2013)"},{"key":"4_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2021.107782","volume":"40","author":"A Tritsarolis","year":"2022","unstructured":"Tritsarolis, A., Kontoulis, Y., Theodoridis, Y.: The Piraeus AIS dataset for large-scale maritime data analytics. Data Brief 40, 107782 (2022)","journal-title":"Data Brief"},{"key":"4_CR23","doi-asserted-by":"crossref","unstructured":"Wiegreffe, S., Pinter, Y.: Attention is not not explanation. arXiv preprint arXiv:1908.04626 (2019)","DOI":"10.18653\/v1\/D19-1002"},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Xing. J., Sieber, R.: The challenges of integrating explainable artificial intelligence into GeoAI. Trans. GIS 27(3), 626\u2013645 (2023)","DOI":"10.1111\/tgis.13045"},{"key":"4_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2021.106153","volume":"158","author":"C Yang","year":"2021","unstructured":"Yang, C., Chen, M., Yuan, Q.: The application of XGBoost and SHAP to examining the factors in freight truck-related crashes: an exploratory analysis. Accid. Anal. Prev. 158, 106153 (2021)","journal-title":"Accid. Anal. Prev."},{"key":"4_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.inffus.2021.11.004","volume":"81","author":"F Zhou","year":"2022","unstructured":"Zhou, F., Wang, T., Zhong, T., Trajcevski, G.: Identifying user geolocation with hierarchical graph neural networks and explainable fusion. Inform. Fusion 81, 1\u201313 (2022)","journal-title":"Inform. Fusion"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Zhou, L., Ma, C., Shi, X., Zhang, D., Li, W., Wu, L.: Salience-cam: visual explanations from convolutional neural networks via salience score. In: 2021 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138. IEEE (2021)","DOI":"10.1109\/IJCNN52387.2021.9534419"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-62269-4_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T14:11:02Z","timestamp":1718892662000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-62269-4_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031622687","9783031622694"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-62269-4_4","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"21 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Science and Information Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"London","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","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":"26 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/Computing","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}