{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:15:16Z","timestamp":1767320116906,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819550111","type":"print"},{"value":"9789819550128","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\/978-981-95-5012-8_11","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:11:48Z","timestamp":1767319908000},"page":"142-151","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ARrec: A GitHub Awesome Repository Recommendation Service Based on Graph Mining"],"prefix":"10.1007","author":[{"given":"Jiaqi","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Yanchun","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Sihan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xiaohan","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Gonzalez, D., Zimmermann, T., Nagappan, N.: The state of the ML-universe: 10 years of Artificial Intelligence & Machine Learning Software Development on GitHub. In: 2020 IEEE\/ACM 17th International Conference on Mining Software Repositories (MSR), pp. 431\u2013442, Seoul, Korea, Republic of (2020)","DOI":"10.1145\/3379597.3387473"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Prana G.A.A., Treude C, Thung F, et al.: Categorizing the Content of GitHub README Files. arXiv e-prints: arXiv: 1802.06997 (2018).","DOI":"10.1007\/s10664-018-9660-3"},{"issue":"17","key":"11_CR3","first-page":"19026","volume":"38","author":"W Su","year":"2024","unstructured":"Su, W., Ai, Q., Li, X., et al.: Wikiformer: pre-training with structured information of wikipedia for ad-hoc retrieval. Proc. AAAI Conf. Artif. Intell. 38(17), 19026\u201319034 (2024)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"issue":"1","key":"11_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10664-024-10576-z","volume":"30","author":"J He","year":"2025","unstructured":"He, J., Xu, B., Yang, Z., et al.: PTM4Tag+: tag recommendation of stack overflow posts with pre-trained models. Empir. Softw. Eng. 30(1), 1\u201341 (2025)","journal-title":"Empir. Softw. Eng."},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Su, X., Khoshgoftaar, T.M.: A survey of collaborative filtering techniques. Adv. Artif. Intell. 2009 (2009)","DOI":"10.1155\/2009\/421425"},{"issue":"3","key":"11_CR6","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1145\/245108.245126","volume":"40","author":"JA Konstan","year":"1997","unstructured":"Konstan, J.A., Miller, B.N., Maltz, D., et al.: Grouplens: applying collaborative filtering to usenet news. Commun. ACM. 40(3), 77\u201387 (1997)","journal-title":"Commun. ACM"},{"key":"11_CR7","volume-title":"Proceedings of International Educational Data Mining Society","author":"A Polyzou","year":"2019","unstructured":"Polyzou, A., Nikolakopoulos, A.N., Karypis, G.: Scholars walk: a markov chain framework for course recommendation. In: Proceedings of International Educational Data Mining Society (2019)"},{"key":"11_CR8","volume-title":"Proceedings of the 4th International Conference on Learning Representations (ICLR)","author":"B Hidasi","year":"2016","unstructured":"Hidasi, B., Karatzoglou, A., Baltrunas, L., Tikk, D.: Session-based recommendations with recurrent neural networks. In: Proceedings of the 4th International Conference on Learning Representations (ICLR) (2016)"},{"key":"11_CR9","first-page":"565","volume-title":"Proceedings of the 11th ACM International Conference on Web Search and Data Mining","author":"J Tang","year":"2018","unstructured":"Tang, J., Wang, K.: Personalized top-n sequential recommendation via convolutional sequence embedding. In: Proceedings of the 11th ACM International Conference on Web Search and Data Mining, pp. 565\u2013573 (2018)"},{"key":"11_CR10","first-page":"197","volume-title":"Proceedings of IEEE International Conference on Data Mining (ICDM)","author":"WC Kang","year":"2018","unstructured":"Kang, W.C., McAuley, J.: Self-attentive sequential recommendation. In: Proceedings of IEEE International Conference on Data Mining (ICDM), pp. 197\u2013206. IEEE (2018)"},{"key":"11_CR11","volume-title":"Proceedings of the 28th ACM International con-Ference on Information and Knowledge Management","author":"F Sun","year":"2019","unstructured":"Sun, F., et al.: Bert4rec: sequential recommendation with bidirectional encoder representations from transformer. In: Proceedings of the 28th ACM International con-Ference on Information and Knowledge Management (2019)"},{"key":"11_CR12","first-page":"135","volume-title":"The 23rd ACM SIGKDD International Conference ACM","author":"Y Dong","year":"2017","unstructured":"Dong, Y., Chawla, N.V., Swami, A.: metapath2vec: scalable representation learning for heterogeneous networks. In: The 23rd ACM SIGKDD International Conference ACM, pp. 135\u2013144 (2017)"},{"key":"11_CR13","unstructured":"Matek, T., Zebec, S.T.: GitHub open source project recommendation system. arXiv:1602.02594."},{"key":"11_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2023.111806","volume":"205","author":"T Wang","year":"2023","unstructured":"Wang, T., Wang, S., Chen, T.H.P.: Study the correlation between the readme file of GitHub projects and their popularity. J. Syst. Softw. 205, 111806 (2023)","journal-title":"J. Syst. Softw."},{"key":"11_CR15","doi-asserted-by":"publisher","first-page":"1296","DOI":"10.1007\/s10664-018-9660-3","volume":"24","author":"GAA Prana","year":"2019","unstructured":"Prana, G.A.A., Treude, C., Thung, F., et al.: Categorizing the content of github readme files. Empir. Softw. Eng. 24, 1296\u20131327 (2019)","journal-title":"Empir. Softw. Eng."},{"key":"11_CR16","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1109\/SANER.2017.7884605","volume-title":"2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER)","author":"Y Zhang","year":"2017","unstructured":"Zhang, Y., Lo, D., Kochhar, P.S., et al.: Detecting similar repositories on GitHub. In: 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 13\u201323. IEEE (2017)"},{"key":"11_CR17","unstructured":"Hamilton, W.L., et al.: Inductive representation learning on large graphs. Neural Inf. Process. Syst. (2017)"},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Perozzi, B., Al-Rfou, R., Skiena, S.: DeepWalk: online learning of social representations. ACM. (2014)","DOI":"10.1145\/2623330.2623732"}],"container-title":["Lecture Notes in Computer Science","Service-Oriented Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5012-8_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T02:11:51Z","timestamp":1767319911000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5012-8_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819550111","9789819550128"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5012-8_11","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":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Service-Oriented Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","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":"1 December 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsoc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icsoc2025.hit.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}