{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T23:43:25Z","timestamp":1767138205799,"version":"build-2238731810"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030185787","type":"print"},{"value":"9783030185794","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-18579-4_2","type":"book-chapter","created":{"date-parts":[[2019,4,23]],"date-time":"2019-04-23T15:05:36Z","timestamp":1556031936000},"page":"20-35","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["An Exploration of Cross-Modal Retrieval for Unseen Concepts"],"prefix":"10.1007","author":[{"given":"Fangming","family":"Zhong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhikui","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Geyong","family":"Min","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,4,24]]},"reference":[{"issue":"6","key":"2_CR1","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1162\/089976603321780317","volume":"15","author":"M Belkin","year":"2003","unstructured":"Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput. 15(6), 1373\u20131396 (2003)","journal-title":"Neural Comput."},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Cao, Y., Long, M., Wang, J., Liu, S.: Collective deep quantization for efficient cross-modal retrieval. In: AAAI, pp. 3974\u20133980 (2017)","DOI":"10.1609\/aaai.v31i1.11218"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Changpinyo, S., Chao, W.L., Gong, B., Sha, F.: Synthesized classifiers for zero-shot learning. In: CVPR, pp. 5327\u20135336 (2016)","DOI":"10.1109\/CVPR.2016.575"},{"key":"2_CR4","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1007\/978-981-10-8530-7_20","volume-title":"Internet Multimedia Computing and Service","author":"J Chi","year":"2018","unstructured":"Chi, J., Huang, X., Peng, Y.: Zero-shot cross-media retrieval with external knowledge. In: Huet, B., Nie, L., Hong, R. (eds.) ICIMCS 2017. CCIS, vol. 819, pp. 200\u2013211. Springer, Singapore (2018). https:\/\/doi.org\/10.1007\/978-981-10-8530-7_20"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Ding, G., Guo, Y., Zhou, J.: Collective matrix factorization hashing for multimodal data. In: CVPR, pp. 2075\u20132082 (2014)","DOI":"10.1109\/CVPR.2014.267"},{"issue":"3","key":"2_CR6","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1109\/TMM.2016.2625747","volume":"19","author":"K Ding","year":"2017","unstructured":"Ding, K., Fan, B., Huo, C., Xiang, S., Pan, C.: Cross-modal hashing via rank-order preserving. IEEE Trans. Multimedia 19(3), 571\u2013585 (2017). https:\/\/doi.org\/10.1109\/TMM.2016.2625747","journal-title":"IEEE Trans. Multimedia"},{"issue":"2","key":"2_CR7","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham, M., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The Pascal visual object classes (VOC) challenge. Int. J. Comput. Vis. 88(2), 303\u2013338 (2010)","journal-title":"Int. J. Comput. Vis."},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Guo, Y., Ding, G., Han, J., Gao, Y.: SitNet: discrete similarity transfer network for zero-shot hashing. In: IJCAI, pp. 1767\u20131773 (2017)","DOI":"10.24963\/ijcai.2017\/245"},{"issue":"6","key":"2_CR9","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1109\/TPAMI.2011.190","volume":"34","author":"SJ Hwang","year":"2012","unstructured":"Hwang, S.J., Grauman, K.: Reading between the lines: object localization using implicit cues from image tags. IEEE Trans. Pattern Anal. Mach. Intell. 34(6), 1145\u20131158 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2_CR10","unstructured":"Ji, Z., Sun, Y., Yu, Y., Pang, Y., Han, J.: Attribute-guided network for cross-modal zero-shot hashing. arXiv preprint arXiv:1802.01943 (2018)"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Jiang, Q.Y., Li, W.J.: Deep cross-modal hashing. In: CVPR, pp. 3270\u20133278 (2017)","DOI":"10.1109\/CVPR.2017.348"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Kodirov, E., Xiang, T., Fu, Z., Gong, S.: Unsupervised domain adaptation for zero-shot learning. In: CVPR, pp. 2452\u20132460 (2015)","DOI":"10.1109\/ICCV.2015.282"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Kodirov, E., Xiang, T., Gong, S.: Semantic autoencoder for zero-shot learning. In: CVPR, pp. 3174\u20133183 (2017)","DOI":"10.1109\/CVPR.2017.473"},{"key":"2_CR14","unstructured":"Liu, H., Ji, R., Wu, Y., Hua, G.: Supervised matrix factorization for cross-modality hashing. In: IJCAI, pp. 1767\u20131773 (2016)"},{"issue":"1","key":"2_CR15","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1109\/TIP.2016.2619262","volume":"26","author":"L Liu","year":"2017","unstructured":"Liu, L., Lin, Z., Shao, L., Shen, F., Ding, G., Han, J.: Sequential discrete hashing for scalable cross-modality similarity retrieval. IEEE Trans. Image Process. 26(1), 107\u2013118 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Long, Y., Liu, L., Shao, L.: Towards fine-grained open zero-shot learning: inferring unseen visual features from attributes. In: IEEE Winter Conference on Applications of Computer Vision, pp. 944\u2013952 (2017)","DOI":"10.1109\/WACV.2017.110"},{"issue":"3","key":"2_CR17","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1023\/A:1011139631724","volume":"42","author":"A Oliva","year":"2001","unstructured":"Oliva, A., Torralba, A.: Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vis. 42(3), 145\u2013175 (2001)","journal-title":"Int. J. Comput. Vis."},{"key":"2_CR18","doi-asserted-by":"publisher","first-page":"2137","DOI":"10.1016\/j.neucom.2017.10.061","volume":"275","author":"S Pachori","year":"2018","unstructured":"Pachori, S., Deshpande, A., Raman, S.: Hashing in the zero shot framework with domain adaptation. Neurocomputing 275, 2137\u20132149 (2018)","journal-title":"Neurocomputing"},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.: GloVe: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"2_CR20","doi-asserted-by":"crossref","unstructured":"Rasiwasia, N., et al.: A new approach to cross-modal multimedia retrieval. In: Proceedings of the 18th ACM International Conference on Multimedia, pp. 251\u2013260 (2010)","DOI":"10.1145\/1873951.1873987"},{"key":"2_CR21","unstructured":"Romera-Paredes, B., Torr, P.: An embarrassingly simple approach to zero-shot learning. In: International Conference on Machine Learning, pp. 2152\u20132161 (2015)"},{"key":"2_CR22","doi-asserted-by":"crossref","unstructured":"Shen, F., Shen, C., Liu, W., Tao Shen, H.: Supervised discrete hashing. In: CVPR, pp. 37\u201345 (2015)","DOI":"10.1109\/CVPR.2015.7298598"},{"issue":"7","key":"2_CR23","doi-asserted-by":"publisher","first-page":"3157","DOI":"10.1109\/TIP.2016.2564638","volume":"25","author":"J Tang","year":"2016","unstructured":"Tang, J., Wang, K., Shao, L.: Supervised matrix factorization hashing for cross-modal retrieval. IEEE Trans. Image Process. 25(7), 3157\u20133166 (2016)","journal-title":"IEEE Trans. Image Process."},{"issue":"10","key":"2_CR24","doi-asserted-by":"publisher","first-page":"2010","DOI":"10.1109\/TPAMI.2015.2505311","volume":"38","author":"K Wang","year":"2016","unstructured":"Wang, K., He, R., Wang, L., Wang, W., Tan, T.: Joint feature selection and subspace learning for cross-modal retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 38(10), 2010\u20132023 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2_CR25","doi-asserted-by":"crossref","unstructured":"Xian, Y., Schiele, B., Akata, Z.: Zero-shot learning-the good, the bad and the ugly. In: CVPR, pp. 4582\u20134591 (2017)","DOI":"10.1109\/CVPR.2017.328"},{"key":"2_CR26","doi-asserted-by":"crossref","unstructured":"Xu, X., Shen, F., Yang, Y., Zhang, D., Shen, H.T., Song, J.: Matrix tri-factorization with manifold regularizations for zero-shot learning. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.217"},{"key":"2_CR27","doi-asserted-by":"crossref","unstructured":"Xu, Y., Yang, Y., Shen, F., Xu, X., Zhou, Y., Shen, H.T.: Attribute hashing for zero-shot image retrieval. In: IEEE International Conference on Multimedia and Expo, pp. 133\u2013138 (2017)","DOI":"10.1109\/ICME.2017.8019425"},{"key":"2_CR28","doi-asserted-by":"crossref","unstructured":"Yang, E., Deng, C., Liu, W., Liu, X., Tao, D., Gao, X.: Pairwise relationship guided deep hashing for cross-modal retrieval. In: AAAI, pp. 1618\u20131625 (2017)","DOI":"10.1609\/aaai.v31i1.10719"},{"key":"2_CR29","doi-asserted-by":"crossref","unstructured":"Yang, Y., Luo, Y., Chen, W., Shen, F., Shao, J., Shen, H.T.: Zero-shot hashing via transferring supervised knowledge. In: Proceedings of the 2016 ACM on Multimedia Conference, pp. 1286\u20131295 (2016)","DOI":"10.1145\/2964284.2964319"},{"key":"2_CR30","doi-asserted-by":"crossref","unstructured":"Zhang, L., Ma, B., He, J., Li, G., Huang, Q., Tian, Q.: Adaptively unified semi-supervised learning for cross-modal retrieval. In: AAAI, pp. 3406\u20133412 (2017)","DOI":"10.24963\/ijcai.2017\/476"},{"issue":"1","key":"2_CR31","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1109\/TMM.2017.2723841","volume":"20","author":"L Zhang","year":"2018","unstructured":"Zhang, L., Ma, B., Li, G., Huang, Q., Tian, Q.: Generalized semi-supervised and structured subspace learning for cross-modal retrieval. IEEE Trans. Multimedia 20(1), 128\u2013141 (2018)","journal-title":"IEEE Trans. Multimedia"},{"key":"2_CR32","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1016\/j.patcog.2018.05.018","volume":"83","author":"F Zhong","year":"2018","unstructured":"Zhong, F., Chen, Z., Min, G.: Deep discrete cross-modal hashing for cross-media retrieval. Pattern Recogn. 83, 64\u201377 (2018)","journal-title":"Pattern Recogn."},{"key":"2_CR33","doi-asserted-by":"crossref","unstructured":"Zhou, J., Ding, G., Guo, Y.: Latent semantic sparse hashing for cross-modal similarity search. In: Proceedings of the 37th ACM International Conference on Research and Development in Information Retrieval, pp. 415\u2013424 (2014)","DOI":"10.1145\/2600428.2609610"}],"updated-by":[{"DOI":"10.1007\/978-3-030-18579-4_46","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2019,6,5]],"date-time":"2019-06-05T00:00:00Z","timestamp":1559692800000}}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-18579-4_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T08:47:35Z","timestamp":1710233255000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-18579-4_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030185787","9783030185794"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-18579-4_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"24 April 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"5 June 2019","order":2,"name":"change_date","label":"Change Date","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Correction","order":3,"name":"change_type","label":"Change Type","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"In the original version of the chapter titled \u201cAn Exploration of Cross-Modal Retrieval for Unseen Concepts\u201d, the acknowledgement was missing. It has been added.","order":4,"name":"change_details","label":"Change Details","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"In the original version of the chapter titled \u201cTowards both Local and Global Query Result Diversification\u201d, the funding information in the acknowledgement section was incomplete. This has now been corrected.","order":5,"name":"change_details","label":"Change Details","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chiang Mai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dasfaa2019.eng.cmu.ac.th\/","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"501","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":"92","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":"64","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":"18% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13 demo papers, 6 tutorial papers","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)"}}]}}