{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:32:27Z","timestamp":1742913147379,"version":"3.40.3"},"publisher-location":"Cham","reference-count":57,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031429347"},{"type":"electronic","value":"9783031429354"}],"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\/978-3-031-42935-4_4","type":"book-chapter","created":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T19:01:38Z","timestamp":1694026898000},"page":"39-49","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Promise of\u00a0Query Answering Systems in\u00a0Sexuality Studies: Current State, Challenges and\u00a0Limitations"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3458-0694","authenticated-orcid":false,"given":"Andrea","family":"Morales-Garz\u00f3n","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2578-0560","authenticated-orcid":false,"given":"Gracia M.","family":"S\u00e1nchez-P\u00e9rez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5593-9803","authenticated-orcid":false,"given":"Juan Carlos","family":"Sierra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6973-477X","authenticated-orcid":false,"given":"Maria J.","family":"Martin-Bautista","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,7]]},"reference":[{"key":"4_CR1","doi-asserted-by":"crossref","unstructured":"Al-Asadi, M.A., Tasdemir, S.: Using artificial intelligence against the phenomenon of fake news: a systematic literature review. In: Combating Fake News with Computational Intelligence Techniques, pp. 39\u201354 (2022)","DOI":"10.1007\/978-3-030-90087-8_2"},{"issue":"6","key":"4_CR2","doi-asserted-by":"publisher","first-page":"273","DOI":"10.3390\/info13060273","volume":"13","author":"F Alkomah","year":"2022","unstructured":"Alkomah, F., Ma, X.: A literature review of textual hate speech detection methods and datasets. Information 13(6), 273 (2022)","journal-title":"Information"},{"issue":"10","key":"4_CR3","doi-asserted-by":"publisher","first-page":"63","DOI":"10.3390\/mti5100063","volume":"5","author":"C Arcila-Calder\u00f3n","year":"2021","unstructured":"Arcila-Calder\u00f3n, C., Amores, J.J., S\u00e1nchez-Holgado, P., Blanco-Herrero, D.: Using shallow and deep learning to automatically detect hate motivated by gender and sexual orientation on twitter in Spanish. Multimodal Technol. Interact. 5(10), 63 (2021)","journal-title":"Multimodal Technol. Interact."},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Belcher, R.E., et al.: A qualitative analysis of female reddit users\u2019 experiences with low libido: how do women perceive their changes in sexual desire? J. Sexual Med. (2023)","DOI":"10.1093\/jsxmed\/qdac045"},{"key":"4_CR5","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., et al.: Language models are few-shot learners. Adv. Neural. Inf. Process. Syst. 33, 1877\u20131901 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"1","key":"4_CR6","first-page":"21","volume":"13","author":"MEF Casta\u00f1o","year":"2008","unstructured":"Casta\u00f1o, M.E.F., Espada, A.A.: Primer estudio psicom\u00e9trico de la versi\u00f3n espa\u00f1ola del agressive sexual behavior inventory (asbi). Revista de psicopatolog\u00eda y psicolog\u00eda cl\u00ednica 13(1), 21\u201331 (2008)","journal-title":"Revista de psicopatolog\u00eda y psicolog\u00eda cl\u00ednica"},{"key":"4_CR7","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.ejmp.2021.02.006","volume":"83","author":"I Castiglioni","year":"2021","unstructured":"Castiglioni, I., et al.: Ai applications to medical images: from machine learning to deep learning. Physica Med. 83, 9\u201324 (2021)","journal-title":"Physica Med."},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Cervilla, O., Jim\u00e9nez-Ant\u00f3n, E., \u00c1lvarez-Muelas, A., Mangas, P., Granados, R., Sierra, J.C.: Solitary sexual desire: its relation to subjective orgasm experience and sexual arousal in the masturbation context within a Spanish population. In: Healthcare, vol. 11, p. 805. MDPI (2023)","DOI":"10.3390\/healthcare11060805"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Chernyavska, T., Yermakova, A., Kokorina, Y., Kolot, S., Kremenchutska, M.: Sexual satisfaction as a factor of psychological well-being. BRAIN. Broad Res. Artif. Intell. Neurosci. 13(1), 292\u2013307 (2022)","DOI":"10.18662\/brain\/13.1\/285"},{"key":"4_CR10","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/s10815-019-01408-x","volume":"36","author":"CL Curchoe","year":"2019","unstructured":"Curchoe, C.L., Bormann, C.L.: Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018. J. Assist. Reprod. Genet. 36, 591\u2013600 (2019)","journal-title":"J. Assist. Reprod. Genet."},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Das, R., Singh, T.D.: Multimodal sentiment analysis: a survey of methods, trends and challenges. ACM Comput. Surv. (2023)","DOI":"10.1145\/3586075"},{"issue":"3","key":"4_CR12","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1016\/j.rbmo.2021.11.003","volume":"44","author":"I Dimitriadis","year":"2022","unstructured":"Dimitriadis, I., Zaninovic, N., Badiola, A.C., Bormann, C.L.: Artificial intelligence in the embryology laboratory: a review. Reprod. Biomed. Online 44(3), 435\u2013448 (2022)","journal-title":"Reprod. Biomed. Online"},{"key":"4_CR13","unstructured":"Divita, G., et al.: Extracting sexual trauma mentions from electronic medical notes using natural language processing. In: MEDINFO 2017: Precision Healthcare Through Informatics: Proceedings of the 16th World Congress on Medical and Health Informatics, vol. 245, p. 351. IOS Press (2018)"},{"issue":"4","key":"4_CR14","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1002\/uog.22122","volume":"56","author":"L Drukker","year":"2020","unstructured":"Drukker, L., Noble, J., Papageorghiou, A.: Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology. Ultrasound Obstetrics Gynecol. 56(4), 498\u2013505 (2020)","journal-title":"Ultrasound Obstetrics Gynecol."},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Eloundou, T., Manning, S., Mishkin, P., Rock, D.: GPTS are GPTS: an early look at the labor market impact potential of large language models (2023)","DOI":"10.1126\/science.adj0998"},{"issue":"9","key":"4_CR16","doi-asserted-by":"publisher","first-page":"2641","DOI":"10.1093\/humrep\/des219","volume":"27","author":"ES Filho","year":"2012","unstructured":"Filho, E.S., Noble, J.A., Poli, M., Griffiths, T., Emerson, G., Wells, D.: A method for semi-automatic grading of human blastocyst microscope images. Hum. Reprod. 27(9), 2641\u20132648 (2012)","journal-title":"Hum. Reprod."},{"key":"4_CR17","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s10506-017-9212-y","volume":"25","author":"L Frank","year":"2017","unstructured":"Frank, L., Nyholm, S.: Robot sex and consent: is consent to sex between a robot and a human conceivable, possible, and desirable? Artif. Intell. Law 25, 305\u2013323 (2017)","journal-title":"Artif. Intell. Law"},{"issue":"1","key":"4_CR18","first-page":"1","volume":"3","author":"Y Gu","year":"2021","unstructured":"Gu, Y., et al.: Domain-specific language model pretraining for biomedical natural language processing. ACM Trans. Comput. Healthc. (HEALTH) 3(1), 1\u201323 (2021)","journal-title":"ACM Trans. Comput. Healthc. (HEALTH)"},{"key":"4_CR19","first-page":"128","volume":"238","author":"AV Gundlapalli","year":"2017","unstructured":"Gundlapalli, A.V., et al.: Using structured and unstructured data to refine estimates of military sexual trauma status among us military veterans. Stud. Health Technol. Inform. 238, 128 (2017)","journal-title":"Stud. Health Technol. Inform."},{"key":"4_CR20","doi-asserted-by":"publisher","first-page":"S149","DOI":"10.1097\/MLR.0000000000001031","volume":"57","author":"AV Gundlapalli","year":"2019","unstructured":"Gundlapalli, A.V., et al.: Combining natural language processing of electronic medical notes with administrative data to determine racial\/ethnic differences in the disclosure and documentation of military sexual trauma in veterans. Med. Care 57, S149\u2013S156 (2019)","journal-title":"Med. Care"},{"issue":"3","key":"4_CR21","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1109\/69.506706","volume":"8","author":"J Han","year":"1996","unstructured":"Han, J., Huang, Y., Cercone, N., Fu, Y.: Intelligent query answering by knowledge discovery techniques. IEEE Trans. Knowl. Data Eng. 8(3), 373\u2013390 (1996)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"4_CR22","unstructured":"Hyde, J.S., DeLamater, J.D.: Understanding Human Sexuality, 9th edn. McGraw-Hill, New York (2006)"},{"key":"4_CR23","doi-asserted-by":"crossref","unstructured":"Istaiteh, O., Al-Omoush, R., Tedmori, S.: Racist and sexist hate speech detection: literature review. In: 2020 International Conference on Intelligent Data Science Technologies and Applications (IDSTA), pp. 95\u201399. IEEE (2020)","DOI":"10.1109\/IDSTA50958.2020.9264052"},{"key":"4_CR24","unstructured":"Jones, A.L., et al.: Regional variations in documentation of sexual trauma concepts in electronic medical records in the united states veterans health administration. In: AMIA Annual Symposium Proceedings, vol. 2019, p. 514. American Medical Informatics Association (2019)"},{"key":"4_CR25","first-page":"1","volume":"9","author":"SA Khanam","year":"2019","unstructured":"Khanam, S.A., Liu, F., Chen, Y.P.P.: Comprehensive structured knowledge base system construction with natural language presentation. HCIS 9, 1\u201332 (2019)","journal-title":"HCIS"},{"key":"4_CR26","unstructured":"Liu, L., et al.: Multi-task learning via adaptation to similar tasks for mortality prediction of diverse rare diseases. In: AMIA Annual Symposium Proceedings, vol. 2020, p. 763. American Medical Informatics Association (2020)"},{"issue":"1","key":"4_CR27","doi-asserted-by":"publisher","first-page":"9599","DOI":"10.1038\/s41598-022-13642-y","volume":"12","author":"YS Liu","year":"2022","unstructured":"Liu, Y.S., Hankey, J.R., Chokka, S., Chokka, P.R., Cao, B.: Individualized identification of sexual dysfunction of psychiatric patients with machine-learning. Sci. Rep. 12(1), 9599 (2022)","journal-title":"Sci. Rep."},{"key":"4_CR28","unstructured":"Lommatzsch, A., Katins, J.: An information retrieval-based approach for building intuitive chatbots for large knowledge bases. In: LWDA, pp. 343\u2013352 (2019)"},{"key":"4_CR29","unstructured":"Magnini, B., Lavelli, A., Fabien, G., Cabrio, E., Cojan, J., Palmero Aprosio, A.: Open domain question answering: techniques, systems and evaluation. In: Tutorial of the Conference on Recent Advances in Natural Language Processing-RANLP, Borovetz, Bulgaria (2005)"},{"issue":"4","key":"4_CR30","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1002\/mar.21619","volume":"39","author":"MM Mariani","year":"2022","unstructured":"Mariani, M.M., Perez-Vega, R., Wirtz, J.: Ai in marketing, consumer research and psychology: a systematic literature review and research agenda. Psychol. Mark. 39(4), 755\u2013776 (2022)","journal-title":"Psychol. Mark."},{"key":"4_CR31","unstructured":"Mart\u00ednez-Barco, P., Vicedo, J.L., Saquete Bor\u00f3, E., Tom\u00e1s, D., et al.: Sistemas de pregunta-respuesta (2007)"},{"issue":"5","key":"4_CR32","doi-asserted-by":"publisher","first-page":"e221","DOI":"10.1016\/S2589-7500(20)30065-0","volume":"2","author":"MD McCradden","year":"2020","unstructured":"McCradden, M.D., Joshi, S., Mazwi, M., Anderson, J.A.: Ethical limitations of algorithmic fairness solutions in health care machine learning. Lancet Digit. Health 2(5), e221\u2013e223 (2020)","journal-title":"Lancet Digit. Health"},{"key":"4_CR33","doi-asserted-by":"crossref","unstructured":"McGahuey, A., et al.: The Arizona sexual experience scale (ASEX): reliability and validity. J. Sex Marital Therapy 26(1), 25\u201340 (2000)","DOI":"10.1080\/009262300278623"},{"issue":"3","key":"4_CR34","doi-asserted-by":"publisher","first-page":"1820","DOI":"10.3390\/ijerph20031820","volume":"20","author":"LE Mu\u00f1oz-Garc\u00eda","year":"2023","unstructured":"Mu\u00f1oz-Garc\u00eda, L.E., G\u00f3mez-Berrocal, C., Guill\u00e9n-Riquelme, A., Sierra, J.C.: Measurement invariance across sexual orientation for measures of sexual attitudes. Int. J. Environ. Res. Publ. Health 20(3), 1820 (2023)","journal-title":"Int. J. Environ. Res. Publ. Health"},{"key":"4_CR35","doi-asserted-by":"crossref","unstructured":"Mu\u00f1oz-Garc\u00eda, L.E., G\u00f3mez-Berrocal, C., Sierra, J.C.: Evaluating the subjective orgasm experience through sexual context, gender, and sexual orientation. Arch. Sexual Behav. 1\u201313 (2022)","DOI":"10.1007\/s10508-022-02493-3"},{"issue":"3","key":"4_CR36","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1136\/bmjsrh-2018-200271","volume":"46","author":"T Nadarzynski","year":"2020","unstructured":"Nadarzynski, T., Bayley, J., Llewellyn, C., Kidsley, S., Graham, C.A.: Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice. BMJ Sexual Reprod. Health 46(3), 210\u2013217 (2020)","journal-title":"BMJ Sexual Reprod. Health"},{"key":"4_CR37","doi-asserted-by":"crossref","unstructured":"Parihar, A.S., Thapa, S., Mishra, S.: Hate speech detection using natural language processing: applications and challenges. In: 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), pp. 1302\u20131308. IEEE (2021)","DOI":"10.1109\/ICOEI51242.2021.9452882"},{"issue":"12","key":"4_CR38","doi-asserted-by":"publisher","first-page":"2716","DOI":"10.1093\/jamia\/ocab170","volume":"28","author":"BG Patra","year":"2021","unstructured":"Patra, B.G., et al.: Extracting social determinants of health from electronic health records using natural language processing: a systematic review. J. Am. Med. Inform. Assoc. 28(12), 2716\u20132727 (2021)","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"8","key":"4_CR39","first-page":"9","volume":"1","author":"A Radford","year":"2019","unstructured":"Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., et al.: Language models are unsupervised multitask learners. OpenAI blog 1(8), 9 (2019)","journal-title":"OpenAI blog"},{"key":"4_CR40","doi-asserted-by":"crossref","unstructured":"Robertson, C., Mukherjee, G., Gooding, H., Kandaswamy, S., Orenstein, E.: A method to advance adolescent sexual health research: automated algorithm finds sexual history documentation. Front. Digit. Health 4 (2022)","DOI":"10.3389\/fdgth.2022.836733"},{"key":"4_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2019.108768","volume":"122","author":"NM Safdar","year":"2020","unstructured":"Safdar, N.M., Banja, J.D., Meltzer, C.C.: Ethical considerations in artificial intelligence. Eur. J. Radiol. 122, 108768 (2020)","journal-title":"Eur. J. Radiol."},{"key":"4_CR42","unstructured":"S\u00e1nchez Fuentes, M., Moyano, N., Granados, R., Sierra Freire, J.C., et al.: Validation of the Spanish version of the Arizona sexual experience scale (ASEX) using self-reported and psychophysiological measures (2019)"},{"key":"4_CR43","unstructured":"Scao, T.L., et al.: Bloom: a 176b-parameter open-access multilingual language model. arXiv preprint arXiv:2211.05100 (2022)"},{"key":"4_CR44","doi-asserted-by":"crossref","unstructured":"Schmidt, A., Wiegand, M.: A survey on hate speech detection using natural language processing. In: Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media, pp. 1\u201310 (2017)","DOI":"10.18653\/v1\/W17-1101"},{"key":"4_CR45","doi-asserted-by":"crossref","unstructured":"Shahid, W., et al.: Detecting and mitigating the dissemination of fake news: challenges and future research opportunities. IEEE Tran. Comput. Soc. Syst. (2022)","DOI":"10.1109\/TCSS.2022.3177359"},{"issue":"1","key":"4_CR46","doi-asserted-by":"publisher","first-page":"69","DOI":"10.2466\/PR0.105.1.69-79","volume":"105","author":"JC Sierra","year":"2009","unstructured":"Sierra, J.C., Guti\u00e9rrez-Quintanilla, R., Berm\u00fadez, M.P., Buela-Casal, G.: Male sexual coercion: analysis of a few associated factors. Psychol. Rep. 105(1), 69\u201379 (2009)","journal-title":"Psychol. Rep."},{"key":"4_CR47","doi-asserted-by":"crossref","unstructured":"Sinclair, D., Dowdeswell, T., Goltz, N.: Artificially intelligent sex bots and female slavery: social science and Jewish legal and ethical perspectives. Inf. Commun. Technol. Law, 1\u201328 (2022)","DOI":"10.1080\/13600834.2022.2154050"},{"key":"4_CR48","doi-asserted-by":"publisher","first-page":"131440","DOI":"10.1109\/ACCESS.2021.3113172","volume":"9","author":"V Socatiyanurak","year":"2021","unstructured":"Socatiyanurak, V., et al.: Law-U: legal guidance through artificial intelligence chatbot for sexual violence victims and survivors. IEEE Access 9, 131440\u2013131461 (2021)","journal-title":"IEEE Access"},{"key":"4_CR49","doi-asserted-by":"crossref","unstructured":"Sprecher, S., McKinney, K.: Sexuality, vol. 6. Sage, Thousand Oaks (1993)","DOI":"10.4135\/9781483326252"},{"key":"4_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpa.2022.100319","volume":"13","author":"FK Sufi","year":"2022","unstructured":"Sufi, F.K.: Ai-socialdisaster: an AI-based software for identifying and analyzing natural disasters from social media. Softw. Impacts 13, 100319 (2022)","journal-title":"Softw. Impacts"},{"key":"4_CR51","doi-asserted-by":"crossref","unstructured":"Thorne, J., Yazdani, M., Saeidi, M., Silvestri, F., Riedel, S., Halevy, A.: From natural language processing to neural databases. In: Proceedings of the VLDB Endowment, vol. 14, pp. 1033\u20131039. VLDB Endowment (2021)","DOI":"10.14778\/3447689.3447706"},{"issue":"5","key":"4_CR52","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1177\/02654075211047004","volume":"39","author":"LM Vowels","year":"2022","unstructured":"Vowels, L.M., Vowels, M.J., Mark, K.P.: Identifying the strongest self-report predictors of sexual satisfaction using machine learning. J. Soc. Pers. Relat. 39(5), 1191\u20131212 (2022)","journal-title":"J. Soc. Pers. Relat."},{"issue":"4","key":"4_CR53","doi-asserted-by":"publisher","first-page":"R139","DOI":"10.1530\/REP-18-0523","volume":"158","author":"R Wang","year":"2019","unstructured":"Wang, R., et al.: Artificial intelligence in reproductive medicine. Reproduction (Cambridge, England) 158(4), R139 (2019)","journal-title":"Reproduction (Cambridge, England)"},{"issue":"1\u20132","key":"4_CR54","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3233\/DS-170007","volume":"1","author":"X Wilcke","year":"2017","unstructured":"Wilcke, X., Bloem, P., De Boer, V.: The knowledge graph as the default data model for learning on heterogeneous knowledge. Data Sci. 1(1\u20132), 39\u201357 (2017)","journal-title":"Data Sci."},{"key":"4_CR55","unstructured":"World Health Organization: Sexual Health. WHO Press (2006)"},{"key":"4_CR56","unstructured":"World Health Organization: Sexual and Reproductive Health and Research (SRH). WHO Press (2020)"},{"key":"4_CR57","doi-asserted-by":"crossref","unstructured":"Zhou, B., Yang, G., Shi, Z., Ma, S.: Natural language processing for smart healthcare. IEEE Rev. Biomed. Eng. (2022)","DOI":"10.1109\/RBME.2022.3210270"}],"container-title":["Lecture Notes in Computer Science","Flexible Query Answering Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-42935-4_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T16:13:27Z","timestamp":1730045607000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-42935-4_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031429347","9783031429354"],"references-count":57,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-42935-4_4","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":"7 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"FQAS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Flexible Query Answering Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mallorca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","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":"5 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"fqas2023","order":10,"name":"conference_id","label":"Conference ID","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":"26","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":"24","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":"92% - 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","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":"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)"}}]}}