{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:38:51Z","timestamp":1742913531764,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030600280"},{"type":"electronic","value":"9783030600297"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-60029-7_20","type":"book-chapter","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T23:07:40Z","timestamp":1600729660000},"page":"215-222","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["DSQA: A Domain Specific QA System for Smart Health Based on Knowledge Graph"],"prefix":"10.1007","author":[{"given":"Ming","family":"Sheng","sequence":"first","affiliation":[]},{"given":"Anqi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yuelin","family":"Bu","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Dong","sequence":"additional","affiliation":[]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Chunxiao","family":"Xing","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"key":"20_CR1","doi-asserted-by":"publisher","unstructured":"Alqifari, R.: Question answering systems approaches and challenges. In: Student Research Workshop, pp. 69\u201375 (2019). https:\/\/doi.org\/10.26615\/issn.2603-2821.2019_011","DOI":"10.26615\/issn.2603-2821.2019_011"},{"key":"20_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1007\/978-3-030-30952-7_52","volume-title":"Web Information Systems and Applications","author":"S Ansong","year":"2019","unstructured":"Ansong, S., Eteffa, K.F., Li, C., Sheng, M., Zhang, Y., Xing, C.: How to empower disease diagnosis in a medical education system using knowledge graph. In: Ni, W., Wang, X., Song, W., Li, Y. (eds.) WISA 2019. LNCS, vol. 11817, pp. 518\u2013523. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-30952-7_52"},{"issue":"4","key":"20_CR3","doi-asserted-by":"publisher","first-page":"36:1","DOI":"10.1145\/3326163","volume":"10","author":"X Ao","year":"2019","unstructured":"Ao, X., Shi, H., Wang, J., Zuo, L., Li, H., He, Q.: Large-scale frequent episode mining from complex event sequences with hierarchies. ACM TIST 10(4), 36:1\u201336:26 (2019). https:\/\/doi.org\/10.1145\/3326163","journal-title":"ACM TIST"},{"key":"20_CR4","doi-asserted-by":"publisher","unstructured":"Bao, Q., Ni, L., Liu, J.: HHH: an online medical chatbot system based on knowledge graph and hierarchical bi-directional attention. In: Proceedings of the Australasian Computer Science Week Multiconference, pp. 1\u201310 (2020). https:\/\/doi.org\/10.1145\/3373017.3373049","DOI":"10.1145\/3373017.3373049"},{"issue":"2","key":"20_CR5","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1186\/s12911-019-0761-8","volume":"19","author":"J He","year":"2019","unstructured":"He, J., Fu, M., Tu, M.: Applying deep matching networks to chinese medical question answering: a study and a dataset. BMC Med. Inform. Decis. Mak. 19(2), 52 (2019). https:\/\/doi.org\/10.1186\/s12911-019-0761-8","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"20_CR6","doi-asserted-by":"publisher","unstructured":"Huang, X., Zhang, J., Li, D., Li, P.: Knowledge graph embedding based question answering. In: WSDM, pp. 105\u2013113 (2019). https:\/\/doi.org\/10.1145\/3289600.3290956","DOI":"10.1145\/3289600.3290956"},{"key":"20_CR7","doi-asserted-by":"publisher","unstructured":"Li, C., Hang, S., Chu, D., Zheng, H., Hu, X.: Knowhealth: a knowledge graph based question-answer platform for elderly people. In: EAI (2019). https:\/\/doi.org\/10.4108\/eai.29-6-2019.2282866","DOI":"10.4108\/eai.29-6-2019.2282866"},{"key":"20_CR8","doi-asserted-by":"publisher","unstructured":"Li, M., Huang, M., Zhang, Y., Feng, W.: A DIK-based question-answering architecture with multi-sources data for medical self-service (S). In: Perkusich, A. (ed.) SEKE, pp. 1\u201310 (2019). https:\/\/doi.org\/10.18293\/SEKE2019-112","DOI":"10.18293\/SEKE2019-112"},{"key":"20_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1007\/978-3-319-67964-8_29","volume-title":"Smart Health","author":"H Liu","year":"2017","unstructured":"Liu, H., Hu, Q., Zhang, Y., Xing, C., Sheng, M.: A knowledge-based health question answering system. In: Chen, H., Zeng, D.D., Karahanna, E., Bardhan, I. (eds.) ICSH 2017. LNCS, vol. 10347, pp. 286\u2013291. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67964-8_29"},{"key":"20_CR10","doi-asserted-by":"publisher","unstructured":"Lukovnikov, D., Fischer, A., Lehmann, J., Auer, S.: Neural network-based question answering over knowledge graphs on word and character level. In: WWW, pp. 1211\u20131220 (2017). https:\/\/doi.org\/10.1145\/3038912.3052675","DOI":"10.1145\/3038912.3052675"},{"key":"20_CR11","doi-asserted-by":"publisher","unstructured":"Pampari, A., Raghavan, P., Liang, J., Peng, J.: emrQA: a large corpus for question answering on electronic medical records. arXiv preprint arXiv:1809.00732 (2018). https:\/\/doi.org\/10.18653\/v1\/d18-1258","DOI":"10.18653\/v1\/d18-1258"},{"issue":"1","key":"20_CR12","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1186\/s12911-019-0798-8","volume":"19","author":"T Ruan","year":"2019","unstructured":"Ruan, T., Huang, Y., Liu, X., Xia, Y., Gao, J.: Qanalysis: a question-answer driven analytic tool on knowledge graphs for leveraging electronic medical records for clinical research. BMC Med. Inform. Decis. Mak. 19(1), 82 (2019). https:\/\/doi.org\/10.1186\/s12911-019-0798-8","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Saha, A., Pahuja, V., Khapra, M.M., Sankaranarayanan, K., Chandar, S.: Complex sequential question answering: towards learning to converse over linked question answer pairs with a knowledge graph. In: AAAI (2018)","DOI":"10.1609\/aaai.v32i1.11332"},{"key":"20_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/978-3-030-34482-5_3","volume-title":"Smart Health","author":"M Sheng","year":"2019","unstructured":"Sheng, M., et al.: DEKGB: an extensible framework for health knowledge graph. In: Chen, H., Zeng, D., Yan, X., Xing, C. (eds.) ICSH 2019. LNCS, vol. 11924, pp. 27\u201338. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-34482-5_3"},{"key":"20_CR15","doi-asserted-by":"publisher","unstructured":"Tian, Y., Ma, W., Xia, F., Song, Y.: Chimed: a Chinese medical corpus for question answering. In: BioNLP Workshop and Shared Task, pp. 250\u2013260 (2019). https:\/\/doi.org\/10.18653\/v1\/w19-5027","DOI":"10.18653\/v1\/w19-5027"},{"key":"20_CR16","doi-asserted-by":"publisher","unstructured":"Wu, J., Zhang, Y., Wang, J., Lin, C., Fu, Y., Xing, C.: Scalable metric similarity join using mapreduce. In: ICDE, pp. 1662\u20131665 (2019). https:\/\/doi.org\/10.1109\/ICDE.2019.00167","DOI":"10.1109\/ICDE.2019.00167"},{"key":"20_CR17","doi-asserted-by":"publisher","first-page":"22988","DOI":"10.1109\/ACCESS.2019.2894438","volume":"7","author":"M Zhang","year":"2019","unstructured":"Zhang, M., Tian, G., Zhang, Y.: A home service-oriented question answering system with high accuracy and stability. IEEE Access 7, 22988\u201322999 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2894438","journal-title":"IEEE Access"},{"key":"20_CR18","doi-asserted-by":"publisher","unstructured":"Zhao, K., et al.: Discovering subsequence patterns for next POI recommendation. In: IJCAI, pp. 3216\u20133222 (2020). https:\/\/doi.org\/10.24963\/ijcai.2020\/445","DOI":"10.24963\/ijcai.2020\/445"},{"key":"20_CR19","doi-asserted-by":"publisher","unstructured":"Zheng, W., Cheng, H., Zou, L., Yu, J.X., Zhao, K.: Natural language question\/answering: let users talk with the knowledge graph. In: CIKM, pp. 217\u2013226 (2017). https:\/\/doi.org\/10.1145\/3132847.3132977","DOI":"10.1145\/3132847.3132977"}],"container-title":["Lecture Notes in Computer Science","Web Information Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60029-7_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T11:41:32Z","timestamp":1709811692000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60029-7_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030600280","9783030600297"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60029-7_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Information Systems and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 September 2020","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":"wisa22020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wisa.pmease.cn\/wisa2020\/index.html","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":"CCF Consys","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"165","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":"42","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":"16","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":"25% - 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":"3.6","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":"7.2","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)"}}]}}