{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T01:09:25Z","timestamp":1760404165462,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030295509"},{"type":"electronic","value":"9783030295516"}],"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\/978-3-030-29551-6_3","type":"book-chapter","created":{"date-parts":[[2019,8,20]],"date-time":"2019-08-20T12:04:02Z","timestamp":1566302642000},"page":"24-32","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Semantic Modeling of Textual Relationships in Cross-modal Retrieval"],"prefix":"10.1007","author":[{"given":"Jing","family":"Yu","sequence":"first","affiliation":[]},{"given":"Chenghao","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Zengchang","family":"Qin","sequence":"additional","affiliation":[]},{"given":"Zhuoqian","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Yue","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Zhiguo","family":"Shi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,21]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"Castrejon, L., Aytar, Y., Vondrick, C., Pirsiavash, H., Torralba, A.: Learning aligned cross-modal representations from weakly aligned data. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.321"},{"key":"3_CR2","unstructured":"Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. In: NIPS, pp. 3837\u20133845 (2016)"},{"issue":"2\u20133","key":"3_CR3","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1080\/00437956.1954.11659520","volume":"10","author":"ZS Harris","year":"1954","unstructured":"Harris, Z.S.: Distributional structure. Word 10(2\u20133), 146\u2013162 (1954)","journal-title":"Word"},{"issue":"4","key":"3_CR4","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.knosys.2009.11.010","volume":"23","author":"C Jiang","year":"2010","unstructured":"Jiang, C., Coenen, F., Sanderson, R., Zito, M.: Text classifcation using graph mining-based feature extraction. Knowl. Based Syst. 23(4), 302\u2013308 (2010)","journal-title":"Knowl. Based Syst."},{"issue":"3","key":"3_CR5","first-page":"370","volume":"17","author":"C Kang","year":"2015","unstructured":"Kang, C., Xiang, S., Liao, S., Xu, C., Pan, C.: Learning consistent feature representation for cross-modal multimedia retrieval. TMM 17(3), 370\u2013381 (2015)","journal-title":"TMM"},{"key":"3_CR6","unstructured":"Kumar, V.B.G., Carneiro, G., Reid, I.: Learning local image descriptors with deep siamese and triplet convolutional networks by minimizing global loss functions. In: CVPR, pp. 5385\u20135394 (2016)"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Li, S., Xiao, T., Li, H., Yang, W., Wang, X.: Identity-aware textual-visual matching with latent co-attention. In: ECCV, pp. 1908\u20131917 (2017)","DOI":"10.1109\/ICCV.2017.209"},{"key":"3_CR8","unstructured":"Mihalcea, R., Tarau, P.: Textrank: bringing order into text. In: EMNLP, pp. 404\u2013411 (2004)"},{"issue":"4","key":"3_CR9","doi-asserted-by":"publisher","first-page":"1007","DOI":"10.1007\/s10044-015-0478-y","volume":"19","author":"Z Qin","year":"2016","unstructured":"Qin, Z., Yu, J., Cong, Y., Wan, T.: Topic correlation model for cross-modal multimedia information retrieval. Pattern Anal. Appl. 19(4), 1007\u20131022 (2016)","journal-title":"Pattern Anal. Appl."},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Rasiwasia, N., et al.: A new approach to cross-modal multimedia retrieval. In: ACMMM, pp. 251\u2013260. ACM (2010)","DOI":"10.1145\/1873951.1873987"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Rousseau, F., Vazirgiannis, M.: Graph-of-word and TWIDF: new approach to ad hoc IR. In: CIKM, pp. 59\u201368 (2013)","DOI":"10.1145\/2505515.2505671"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Sharma, A., Kumar, A., Daume, H., Jacobs, D.W.: Generalized multiview analysis: a discriminative latent space. In: CVPR, pp. 2160\u20132167 (2012)","DOI":"10.1109\/CVPR.2012.6247923"},{"key":"3_CR13","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: ICLR (2015)"},{"issue":"10","key":"3_CR14","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/2629489","volume":"57","author":"D Vrande\u010di\u0107","year":"2014","unstructured":"Vrande\u010di\u0107, D., Kr\u00f6tzsch, M.: Wikidata: a free collaborative knowledgebase. Commun. ACM 57(10), 78\u201385 (2014)","journal-title":"Commun. ACM"},{"issue":"10","key":"3_CR15","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. PAMI 38(10), 2010\u20132023 (2016)","journal-title":"PAMI"},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Wang, K., He, R., Wang, W., Wang, L.: Learning coupled feature spaces for cross-modal matching. In: ICCV, pp. 2088\u20132095 (2013)","DOI":"10.1109\/ICCV.2013.261"},{"key":"3_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/978-3-030-00776-8_21","volume-title":"Advances in Multimedia Information Processing \u2013 PCM 2018","author":"J Yu","year":"2018","unstructured":"Yu, J., et al.: Modeling text with graph convolutional network for cross-modal information retrieval. In: Hong, R., Cheng, W.-H., Yamasaki, T., Wang, M., Ngo, C.-W. (eds.) PCM 2018. LNCS, vol. 11164, pp. 223\u2013234. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-030-00776-8_21"},{"key":"3_CR18","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: IJCAI, pp. 3406\u20133412 (2017)","DOI":"10.24963\/ijcai.2017\/476"}],"container-title":["Lecture Notes in Computer Science","Knowledge Science, Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29551-6_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,22]],"date-time":"2020-02-22T09:03:38Z","timestamp":1582362218000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-29551-6_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030295509","9783030295516"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29551-6_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"21 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KSEM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Knowledge Science, Engineering and Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Athens","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","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":"28 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ksem2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ksem.conferences.academy\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"240","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":"77","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":"26","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":"32% - 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":"4","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)"}}]}}