{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,14]],"date-time":"2025-06-14T19:10:09Z","timestamp":1749928209915,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819681693","type":"print"},{"value":"9789819681709","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-8170-9_13","type":"book-chapter","created":{"date-parts":[[2025,6,14]],"date-time":"2025-06-14T18:50:11Z","timestamp":1749927011000},"page":"162-174","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Labor Migration Modeling Through Large-Scale Job Query Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1448-5566","authenticated-orcid":false,"given":"Zhuoning","family":"Guo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0894-9651","authenticated-orcid":false,"given":"Le","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4570-643X","authenticated-orcid":false,"given":"Hengshu","family":"Zhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5085-5216","authenticated-orcid":false,"given":"Weijia","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6016-6465","authenticated-orcid":false,"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2568-5339","authenticated-orcid":false,"given":"Hao","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,15]]},"reference":[{"key":"13_CR1","unstructured":"Abu-El-Haija, S., Perozzi, B., Kapoor, A., Alipourfard, N., Lerman, K., Harutyunyan, H., Ver\u00a0Steeg, G., Galstyan, A.: Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing. In: international conference on machine learning. pp. 21\u201329. PMLR (2019)"},{"issue":"1","key":"13_CR2","first-page":"22","volume":"19","author":"D Card","year":"2001","unstructured":"Card, D.: Immigrant inflows, native outflows, and the local labor market impacts of higher immigration. J. Law Econ. 19(1), 22\u201364 (2001)","journal-title":"J. Law Econ."},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Chao, W., Qiu, Z., Wu, L., Guo, Z., Zheng, Z., Zhu, H., Liu, H.: A cross-view hierarchical graph learning hypernetwork for skill demand-supply joint prediction. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a038, pp. 19813\u201319822 (2024)","DOI":"10.1609\/aaai.v38i18.29956"},{"key":"13_CR4","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.landurbplan.2017.02.014","volume":"162","author":"C Fang","year":"2017","unstructured":"Fang, C., Yu, D.: Urban agglomeration: An evolving concept of an emerging phenomenon. Landsc. Urban Plan. 162, 126\u2013136 (2017)","journal-title":"Landsc. Urban Plan."},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Annals of statistics pp. 1189\u20131232 (2001)","DOI":"10.1214\/aos\/1013203451"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Guo, Z., Liu, H., Zhang, L., Zhang, Q., Zhu, H., Xiong, H.: Talent demand-supply joint prediction with dynamic heterogeneous graph enhanced meta-learning. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. pp. 2957\u20132967 (2022)","DOI":"10.1145\/3534678.3539139"},{"issue":"8","key":"13_CR7","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"13_CR8","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"13_CR9","unstructured":"Li, Y., Yu, R., Shahabi, C., Liu, Y.: Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv preprint arXiv:1707.01926 (2017)"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Lin, A.Y., Cranshaw, J., Counts, S.: Forecasting us domestic migration using internet search queries. In: The world wide web conference. pp. 1061\u20131072 (2019)","DOI":"10.1145\/3308558.3313667"},{"key":"13_CR11","unstructured":"Mamertino, M., Sinclair, T.M.: Online job search and migration intentions across eu member states. Institute for International Economic Policy Working Paper Series (2016)"},{"key":"13_CR12","unstructured":"Martin, P., Abella, M., Kuptsch, C.: Managing labor migration in the twenty-first century. In: Managing Labor Migration in the Twenty-First Century. Yale University Press (2008)"},{"key":"13_CR13","unstructured":"Oreshkin, B.N., Carpov, D., Chapados, N., Bengio, Y.: N-beats: Neural basis expansion analysis for interpretable time series forecasting. arXiv preprint arXiv:1905.10437 (2019)"},{"key":"13_CR14","unstructured":"Pei, H., Wei, B., Chang, K.C.C., Lei, Y., Yang, B.: Geom-gcn: Geometric graph convolutional networks. arXiv preprint arXiv:2002.05287 (2020)"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Perrotta, D., Johnson, S.C., Theile, T., Grow, A., de\u00a0Valk, H., Zagheni, E.: Openness to migrate internationally for a job: evidence from linkedin data in europe. In: Proceedings of the International AAAI Conference on Web and Social Media. vol.\u00a016, pp. 759\u2013769 (2022)","DOI":"10.1609\/icwsm.v16i1.19332"},{"issue":"2","key":"13_CR16","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1038\/s44284-023-00022-4","volume":"1","author":"Y Sun","year":"2024","unstructured":"Sun, Y., Zhu, H., Wang, L., Zhang, L., Xiong, H.: Large-scale online job search behaviors reveal labor market shifts amid covid-19. Nature Cities 1(2), 150\u2013163 (2024)","journal-title":"Nature Cities"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zhu, H., Zhuang, F., Gu, J., He, Q.: Exploring the urban region-of-interest through the analysis of online map search queries. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. pp. 2269\u20132278 (2018)","DOI":"10.1145\/3219819.3220009"},{"issue":"1","key":"13_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40878-021-00273-x","volume":"9","author":"J Tjaden","year":"2021","unstructured":"Tjaden, J.: Measuring migration 2.0: a review of digital data sources. Comparative Migration Studies 9(1), 1\u201320 (2021). https:\/\/doi.org\/10.1186\/s40878-021-00273-x","journal-title":"Comparative Migration Studies"},{"key":"13_CR19","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30 (2017)"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Yu, B., Yin, H., Zhu, Z.: Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting. arXiv preprint arXiv:1709.04875 (2017)","DOI":"10.24963\/ijcai.2018\/505"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhou, D., Zhu, H., Xu, T., Zha, R., Chen, E., Xiong, H.: Attentive heterogeneous graph embedding for job mobility prediction. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. pp. 2192\u20132201 (2021)","DOI":"10.1145\/3447548.3467388"},{"issue":"5","key":"13_CR22","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1109\/TETCI.2021.3100641","volume":"5","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Ti\u0148o, P., Leonardis, A., Tang, K.: A survey on neural network interpretability. IEEE Transactions on Emerging Topics in Computational Intelligence 5(5), 726\u2013742 (2021)","journal-title":"IEEE Transactions on Emerging Topics in Computational Intelligence"},{"issue":"4","key":"13_CR23","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1093\/cep\/byg028","volume":"21","author":"Y Zhao","year":"2003","unstructured":"Zhao, Y.: The role of migrant networks in labor migration: The case of china. Contemp. Econ. Policy 21(4), 500\u2013511 (2003)","journal-title":"Contemp. Econ. Policy"},{"key":"13_CR24","unstructured":"Zheng, X., Liu, Y., Pan, S., Zhang, M., Jin, D., Yu, P.S.: Graph neural networks for graphs with heterophily: A survey. arXiv preprint arXiv:2202.07082 (2022)"},{"key":"13_CR25","first-page":"7793","volume":"33","author":"J Zhu","year":"2020","unstructured":"Zhu, J., Yan, Y., Zhao, L., Heimann, M., Akoglu, L., Koutra, D.: Beyond homophily in graph neural networks: Current limitations and effective designs. Adv. Neural. Inf. Process. Syst. 33, 7793\u20137804 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-8170-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,14]],"date-time":"2025-06-14T18:50:16Z","timestamp":1749927016000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-8170-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819681693","9789819681709"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-8170-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"15 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pakdd2025.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}