{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T08:28:36Z","timestamp":1765268916484,"version":"3.40.3"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031416750"},{"type":"electronic","value":"9783031416767"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-41676-7_9","type":"book-chapter","created":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T07:02:59Z","timestamp":1692342179000},"page":"152-166","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Semantic Graph Representation Learning for\u00a0Handwritten Mathematical Expression Recognition"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-1105-7052","authenticated-orcid":false,"given":"Zhuang","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2822-1564","authenticated-orcid":false,"given":"Ye","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8799-3409","authenticated-orcid":false,"given":"Zhilong","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8940-480X","authenticated-orcid":false,"given":"Jinfeng","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3449-5940","authenticated-orcid":false,"given":"Xiang","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,19]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.patrec.2012.09.023","volume":"35","author":"F Alvaro","year":"2014","unstructured":"Alvaro, F., S\u00e1nchez, J.A., Bened\u00ed, J.M.: Recognition of on-line handwritten mathematical expressions using 2D stochastic context-free grammars and hidden Markov models. Pattern Recogn. Lett. 35, 58\u201367 (2014)","journal-title":"Pattern Recogn. Lett."},{"key":"9_CR2","doi-asserted-by":"crossref","unstructured":"Anderson, R.H.: Syntax-directed recognition of hand-printed two-dimensional mathematics. In: Symposium on Interactive Systems for Experimental Applied Mathematics: Proceedings of the Association for Computing Machinery Inc., Symposium, pp. 436\u2013459 (1967)","DOI":"10.1016\/B978-0-12-395608-8.50048-7"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Bian, X., Qin, B., Xin, X., Li, J., Su, X., Wang, Y.: Handwritten mathematical expression recognition via attention aggregation based bi-directional mutual learning. In: Proceeding of the AAAI Conference on Artificial Intelligence, pp. 113\u2013121 (2022)","DOI":"10.1609\/aaai.v36i1.19885"},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Chan, K.F., Yeung, D.Y.: Elastic structural matching for online handwritten alphanumeric character recognition. In: Proceedings of the Fourteenth International Conference on Pattern Recognition (Cat. No. 98EX170), vol. 2, pp. 1508\u20131511. IEEE (1998)","DOI":"10.1109\/ICPR.1998.711993"},{"issue":"8","key":"9_CR5","doi-asserted-by":"publisher","first-page":"1671","DOI":"10.1016\/S0031-3203(00)00102-3","volume":"34","author":"KF Chan","year":"2001","unstructured":"Chan, K.F., Yeung, D.Y.: Error detection, error correction and performance evaluation in on-line mathematical expression recognition. Pattern Recogn. 34(8), 1671\u20131684 (2001)","journal-title":"Pattern Recogn."},{"key":"9_CR6","unstructured":"Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)"},{"key":"9_CR7","unstructured":"Deng, Y., Kanervisto, A., Ling, J., Rush, A.M.: Image-to-markup generation with coarse-to-fine attention. In: International Conference on Machine Learning, pp. 980\u2013989. PMLR (2017)"},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Fang, S., Xie, H., Wang, Y., Mao, Z., Zhang, Y.: Read like humans: autonomous, bidirectional and iterative language modeling for scene text recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7098\u20137107 (2021)","DOI":"10.1109\/CVPR46437.2021.00702"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Hu, L., Zanibbi, R.: Hmm-based recognition of online handwritten mathematical symbols using segmental k-means initialization and a modified pen-up\/down feature. In: 2011 International Conference on Document Analysis and Recognition, pp. 457\u2013462. IEEE (2011)","DOI":"10.1109\/ICDAR.2011.98"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Keshari, B., Watt, S.: Hybrid mathematical symbol recognition using support vector machines. In: Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), vol. 2, pp. 859\u2013863. IEEE (2007)","DOI":"10.1109\/ICDAR.2007.4377037"},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Kosmala, A., Rigoll, G., Lavirotte, S., Pottier, L.: On-line handwritten formula recognition using hidden Markov models and context dependent graph grammars. In: Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR\u201999 (Cat. No. PR00318), pp. 107\u2013110. IEEE (1999)","DOI":"10.1109\/ICDAR.1999.791736"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Lavirotte, S., Pottier, L.: Mathematical formula recognition using graph grammar. In: Document Recognition, vol. 3305, pp. 44\u201352. International Society for Optics and Photonics (1998)","DOI":"10.1117\/12.304644"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Le, A.D.: Recognizing handwritten mathematical expressions via paired dual loss attention network and printed mathematical expressions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 566\u2013567 (2020)","DOI":"10.1109\/CVPRW50498.2020.00291"},{"key":"9_CR15","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/j.patrec.2019.09.002","volume":"128","author":"AD Le","year":"2019","unstructured":"Le, A.D., Indurkhya, B., Nakagawa, M.: Pattern generation strategies for improving recognition of handwritten mathematical expressions. Pattern Recogn. Lett. 128, 255\u2013262 (2019)","journal-title":"Pattern Recogn. Lett."},{"key":"9_CR16","doi-asserted-by":"publisher","unstructured":"Li, B., et al.: When counting meets HMER: counting-aware network for handwritten mathematical expression recognition. In: Computer Vision-ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XXVIII, pp. 197\u2013214. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19815-1_12","DOI":"10.1007\/978-3-031-19815-1_12"},{"key":"9_CR17","doi-asserted-by":"crossref","unstructured":"Li, Z., Jin, L., Lai, S., Zhu, Y.: Improving attention-based handwritten mathematical expression recognition with scale augmentation and drop attention. arXiv preprint arXiv:2007.10092 (2020)","DOI":"10.1109\/ICFHR2020.2020.00041"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Mouchere, H., Viard-Gaudin, C., Zanibbi, R., Garain, U.: ICFHR 2014 competition on recognition of on-line handwritten mathematical expressions (CROHME 2014). In: Proceeding of the International Conference on Frontiers in Handwriting Recognition, pp. 791\u2013796 (2014)","DOI":"10.1109\/ICFHR.2014.138"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Mouch\u00e8re, H., Viard-Gaudin, C., Zanibbi, R., Garain, U.: ICFHR 2016 CROHME: competition on recognition of online handwritten mathematical expressions. In: Proceeding of the International Conference on Frontiers in Handwriting Recognition, pp. 607\u2013612 (2016)","DOI":"10.1109\/ICFHR.2016.0116"},{"key":"9_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1007\/978-3-030-86159-9_8","volume-title":"Document Analysis and Recognition \u2013 ICDAR 2021 Workshops","author":"CT Nguyen","year":"2021","unstructured":"Nguyen, C.T., Nguyen, H.T., Morizumi, K., Nakagawa, M.: Temporal classification constraint for improving handwritten mathematical expression recognition. In: Barney Smith, E.H., Pal, U. (eds.) ICDAR 2021. LNCS, vol. 12917, pp. 113\u2013125. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86159-9_8"},{"key":"9_CR21","doi-asserted-by":"crossref","unstructured":"Qiao, Z., Zhou, Y., Yang, D., Zhou, Y., Wang, W.: Seed: semantics enhanced encoder-decoder framework for scene text recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13528\u201313537 (2020)","DOI":"10.1109\/CVPR42600.2020.01354"},{"issue":"11","key":"9_CR22","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.1109\/TPAMI.2016.2646371","volume":"39","author":"B Shi","year":"2016","unstructured":"Shi, B., Bai, X., Yao, C.: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE Trans. Pattern Anal. Mach. Intell. 39(11), 2298\u20132304 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"9_CR23","doi-asserted-by":"publisher","first-page":"2035","DOI":"10.1109\/TPAMI.2018.2848939","volume":"41","author":"B Shi","year":"2018","unstructured":"Shi, B., Yang, M., Wang, X., Lyu, P., Yao, C., Bai, X.: ASTER: an attentional scene text recognizer with flexible rectification. IEEE Trans. Pattern Anal. Mach. Intell. 41(9), 2035\u20132048 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9_CR24","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks (2014)"},{"key":"9_CR25","doi-asserted-by":"crossref","unstructured":"Truong, T.N., Nguyen, C.T., Phan, K.M., Nakagawa, M.: Improvement of end-to-end offline handwritten mathematical expression recognition by weakly supervised learning. In: 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 181\u2013186. IEEE (2020)","DOI":"10.1109\/ICFHR2020.2020.00042"},{"issue":"1","key":"9_CR26","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1016\/j.eswa.2009.05.091","volume":"37","author":"BQ Vuong","year":"2010","unstructured":"Vuong, B.Q., He, Y., Hui, S.C.: Towards a web-based progressive handwriting recognition environment for mathematical problem solving. Expert Syst. Appl. 37(1), 886\u2013893 (2010)","journal-title":"Expert Syst. Appl."},{"key":"9_CR27","doi-asserted-by":"crossref","unstructured":"Wang, J., Du, J., Zhang, J., Wang, Z.R.: Multi-modal attention network for handwritten mathematical expression recognition. In: 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 1181\u20131186. IEEE (2019)","DOI":"10.1109\/ICDAR.2019.00191"},{"key":"9_CR28","doi-asserted-by":"crossref","unstructured":"Winkler, H.J.: Hmm-based handwritten symbol recognition using on-line and off-line features. In: 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, vol. 6, pp. 3438\u20133441. IEEE (1996)","DOI":"10.1109\/ICASSP.1996.550767"},{"key":"9_CR29","doi-asserted-by":"crossref","unstructured":"Wu, J.W., Yin, F., Zhang, Y., Zhang, X.Y., Liu, C.L.: Graph-to-Graph: towards accurate and interpretable online handwritten mathematical expression recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 2925\u20132933 (2021)","DOI":"10.1609\/aaai.v35i4.16399"},{"key":"9_CR30","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/978-3-030-10925-7_2","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"J-W Wu","year":"2019","unstructured":"Wu, J.-W., Yin, F., Zhang, Y.-M., Zhang, X.-Y., Liu, C.-L.: Image-to-markup generation via paired adversarial learning. In: Berlingerio, M., Bonchi, F., G\u00e4rtner, T., Hurley, N., Ifrim, G. (eds.) ECML PKDD 2018. LNCS (LNAI), vol. 11051, pp. 18\u201334. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-10925-7_2"},{"key":"9_CR31","doi-asserted-by":"crossref","unstructured":"Wu, J.W., Yin, F., Zhang, Y.M., Zhang, X.Y., Liu, C.L.: Handwritten mathematical expression recognition via paired adversarial learning. Int. J. Comput. Vis. 128(10), 2386\u20132401 (2020)","DOI":"10.1007\/s11263-020-01291-5"},{"key":"9_CR32","unstructured":"Yamamoto, R., Sako, S., Nishimoto, T., Sagayama, S.: On-line recognition of handwritten mathematical expressions based on stroke-based stochastic context-free grammar. In: Tenth International Workshop on Frontiers in Handwriting Recognition. Suvisoft (2006)"},{"key":"9_CR33","doi-asserted-by":"crossref","unstructured":"Yu, D., et al.: Towards accurate scene text recognition with semantic reasoning networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12113\u201312122 (2020)","DOI":"10.1109\/CVPR42600.2020.01213"},{"key":"9_CR34","doi-asserted-by":"crossref","unstructured":"Yuan, Y., et al.: Syntax-aware network for handwritten mathematical expression recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4553\u20134562 (2022)","DOI":"10.1109\/CVPR52688.2022.00451"},{"key":"9_CR35","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/978-3-030-58529-7_9","volume-title":"Computer Vision \u2013 ECCV 2020","author":"X Yue","year":"2020","unstructured":"Yue, X., Kuang, Z., Lin, C., Sun, H., Zhang, W.: RobustScanner: dynamically enhancing positional clues for robust text recognition. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12364, pp. 135\u2013151. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58529-7_9"},{"key":"9_CR36","unstructured":"Zeiler, M.D.: ADADELTA: an adaptive learning rate method. arXiv preprint arXiv:1212.5701 (2012)"},{"key":"9_CR37","doi-asserted-by":"crossref","unstructured":"Zhang, J., Du, J., Dai, L.: Multi-scale attention with dense encoder for handwritten mathematical expression recognition. In: 2018 24th International Conference on Pattern Recognition (ICPR), pp. 2245\u20132250. IEEE (2018)","DOI":"10.1109\/ICPR.2018.8546031"},{"issue":"1","key":"9_CR38","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1109\/TMM.2018.2844689","volume":"21","author":"J Zhang","year":"2018","unstructured":"Zhang, J., Du, J., Dai, L.: Track, Attend, and Parse (TAP): an end-to-end framework for online handwritten mathematical expression recognition. IEEE Trans. Multimedia 21(1), 221\u2013233 (2018)","journal-title":"IEEE Trans. Multimedia"},{"key":"9_CR39","unstructured":"Zhang, J., Du, J., Yang, Y., Song, Y.Z., Wei, S., Dai, L.: A tree-structured decoder for image-to-markup generation. In: International Conference on Machine Learning, pp. 11076\u201311085. PMLR (2020)"},{"key":"9_CR40","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/j.patcog.2017.06.017","volume":"71","author":"J Zhang","year":"2017","unstructured":"Zhang, J., et al.: Watch, attend and parse: an end-to-end neural network based approach to handwritten mathematical expression recognition. Pattern Recogn. 71, 196\u2013206 (2017)","journal-title":"Pattern Recogn."},{"key":"9_CR41","unstructured":"Zhang, Z., He, T., Zhang, H., Zhang, Z., Xie, J., Li, M.: Bag of freebies for training object detection neural networks. arXiv preprint arXiv:1902.04103 (2019)"},{"key":"9_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1007\/978-3-030-86331-9_37","volume-title":"Document Analysis and Recognition \u2013 ICDAR 2021","author":"W Zhao","year":"2021","unstructured":"Zhao, W., Gao, L., Yan, Z., Peng, S., Du, L., Zhang, Z.: Handwritten mathematical expression recognition with bidirectionally trained transformer. In: Llad\u00f3s, J., Lopresti, D., Uchida, S. (eds.) ICDAR 2021. LNCS, vol. 12822, pp. 570\u2013584. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86331-9_37"}],"container-title":["Lecture Notes in Computer Science","Document Analysis and Recognition - ICDAR 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-41676-7_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T09:37:00Z","timestamp":1729935420000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-41676-7_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031416750","9783031416767"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-41676-7_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"19 August 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Document Analysis and Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"San Jos\u00e9, CA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icdar2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icdar2023.org\/","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":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"316","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":"154","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":"49% - 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":"2.89","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":"1.50","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)"}},{"value":"Number and type of other papers accepted : IJDAR track 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)"}}]}}