{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T16:45:52Z","timestamp":1784306752553,"version":"3.55.0"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031189067","type":"print"},{"value":"9783031189074","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-18907-4_26","type":"book-chapter","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:03:53Z","timestamp":1666825433000},"page":"330-343","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Preference-Aware Modality Representation and\u00a0Fusion for\u00a0Micro-video Recommendation"],"prefix":"10.1007","author":[{"given":"Chuanfa","family":"Tian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,27]]},"reference":[{"key":"26_CR1","unstructured":"Arora, S., Liang, Y., Ma, T.: A simple but tough-to-beat baseline for sentence embeddings. In: Proceedings of the International Conference on Learning Representations, pp. 1\u201316 (2017)"},{"key":"26_CR2","doi-asserted-by":"crossref","unstructured":"Bhalse, N., Thakur, R.: Algorithm for movie recommendation system using collaborative filtering. Mater. Today Proc., 1\u20136 (2021)","DOI":"10.1016\/j.matpr.2021.01.235"},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Cai, D., Qian, S., Fang, Q., Hu, J., Ding, W., Xu, C.: Heterogeneous graph contrastive learning network for personalized micro-video recommendation. IEEE Trans. Multimedia (Early Access), 1\u201313 (2022)","DOI":"10.1109\/TMM.2022.3151026"},{"key":"26_CR4","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1109\/TMM.2021.3059508","volume":"24","author":"D Cai","year":"2021","unstructured":"Cai, D., Qian, S., Fang, Q., Xu, C.: Heterogeneous hierarchical feature aggregation network for personalized micro-video recommendation. IEEE Trans. Multimedia 24, 805\u2013818 (2021)","journal-title":"IEEE Trans. Multimedia"},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Davidson, J., et al.: The youtube video recommendation system. In: Proceedings of the ACM Conference on Recommender systems, pp. 293\u2013296 (2010)","DOI":"10.1145\/1864708.1864770"},{"issue":"4","key":"26_CR6","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1007\/s11280-020-00858-z","volume":"24","author":"Y Han","year":"2020","unstructured":"Han, Y., Gu, P., Gao, W., Xu, G., Wu, J.: Aspect-level sentiment capsule network for micro-video click-through rate prediction. World Wide Web 24(4), 1045\u20131064 (2020). https:\/\/doi.org\/10.1007\/s11280-020-00858-z","journal-title":"World Wide Web"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Herlocker, J.L., Konstan, J.A., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 230\u2013237 (1999)","DOI":"10.1145\/312624.312682"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Hershey, S., et al.: CNN architectures for large-scale audio classification. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 131\u2013135 (2017)","DOI":"10.1109\/ICASSP.2017.7952132"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Jin, Y., Xu, J., He, X.: Personalized micro-video recommendation based on multi-modal features and user interest evolution. In: Proceedings of the International Conference on Image and Graphics, pp. 607\u2013618 (2019)","DOI":"10.1007\/978-3-030-34110-7_51"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Lei, C., et al.: Semi: A sequential multi-modal information transfer network for e-commerce micro-video recommendations. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 3161\u20133171 (2021)","DOI":"10.1145\/3447548.3467189"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Liu, M., Nie, L., Wang, M., Chen, B.: Towards micro-video understanding by joint sequential-sparse modeling. In: Proceedings of the ACM International Conference on Multimedia, pp. 970\u2013978 (2017)","DOI":"10.1145\/3123266.3123341"},{"issue":"3","key":"26_CR13","doi-asserted-by":"publisher","first-page":"1235","DOI":"10.1109\/TIP.2018.2875363","volume":"28","author":"M Liu","year":"2018","unstructured":"Liu, M., Nie, L., Wang, X., Tian, Q., Chen, B.: Online data organizer: micro-video categorization by structure-guided multimodal dictionary learning. IEEE Trans. Image Process. 28(3), 1235\u20131247 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Liu, Y., et al.: Concept-aware denoising graph neural network for micro-video recommendation. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 1099\u20131108 (2021)","DOI":"10.1145\/3459637.3482417"},{"issue":"3","key":"26_CR15","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1007\/s41019-019-00101-4","volume":"4","author":"J Ma","year":"2019","unstructured":"Ma, J., Wen, J., Zhong, M., Chen, W., Li, X.: Mmm: multi-source multi-net micro-video recommendation with clustered hidden item representation learning. Data Sci. Eng. 4(3), 240\u2013253 (2019)","journal-title":"Data Sci. Eng."},{"key":"26_CR16","doi-asserted-by":"crossref","unstructured":"Ma, J., Wen, J., Zhong, M., Chen, W., Zhou, X., Indulska, J.: Multi-source multi-net micro-video recommendation with hidden item category discovery. In: International Conference on Database Systems for Advanced Applications, pp. 384\u2013400 (2019)","DOI":"10.1007\/978-3-030-18579-4_23"},{"key":"26_CR17","doi-asserted-by":"crossref","unstructured":"Nie, L., et al.: Enhancing micro-video understanding by harnessing external sounds. In: Proceedings of the ACM International Conference on Multimedia, pp. 1192\u20131200 (2017)","DOI":"10.1145\/3123266.3123313"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Wei, Y., Wang, X., Nie, L., He, X., Hong, R., Chua, T.S.: MMGCN: multi-modal graph convolution network for personalized recommendation of micro-video. In: Proceedings of the ACM International Conference on Multimedia, pp. 1437\u20131445 (2019)","DOI":"10.1145\/3343031.3351034"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18907-4_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:08:06Z","timestamp":1666825686000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18907-4_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031189067","9783031189074"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18907-4_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"27 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/en.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"564","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":"233","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":"41% - 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":"3.03","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":"3.35","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)"}}]}}