Literatura científica selecionada sobre o tema "Text privacy"
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Artigos de revistas sobre o assunto "Text privacy"
Kanyar, Mohammad Naeem. "Differential Privacy “Working Towards Differential Privacy for Sensitive Text “". International Journal of Engineering and Computer Science 12, n.º 04 (2 de abril de 2023): 25691–99. http://dx.doi.org/10.18535/ijecs/v12i04.4727.
Texto completo da fonteShree, A. N. Ramya, e Kiran P. "Privacy Preserving Text Document Summarization". Journal of Engineering Research and Sciences 1, n.º 7 (julho de 2022): 7–14. http://dx.doi.org/10.55708/js0107002.
Texto completo da fonteBihani, Geetanjali. "Interpretable Privacy Preservation of Text Representations Using Vector Steganography". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 11 (28 de junho de 2022): 12872–73. http://dx.doi.org/10.1609/aaai.v36i11.21573.
Texto completo da fonteDopierała, Renata. "Społeczne wyobrażenia prywatności". Kultura i Społeczeństwo 50, n.º 1-2 (30 de março de 2006): 307–19. http://dx.doi.org/10.35757/kis.2006.50.1-2.14.
Texto completo da fonteLiang, Zi, Pinghui Wang, Ruofei Zhang, Nuo Xu, Shuo Zhang, Lifeng Xing, Haitao Bai e Ziyang Zhou. "MERGE: Fast Private Text Generation". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 18 (24 de março de 2024): 19884–92. http://dx.doi.org/10.1609/aaai.v38i18.29964.
Texto completo da fonteWunderlich, Dominik, Daniel Bernau, Francesco Aldà, Javier Parra-Arnau e Thorsten Strufe. "On the Privacy–Utility Trade-Off in Differentially Private Hierarchical Text Classification". Applied Sciences 12, n.º 21 (4 de novembro de 2022): 11177. http://dx.doi.org/10.3390/app122111177.
Texto completo da fontePang, Hweehwa, Jialie Shen e Ramayya Krishnan. "Privacy-preserving similarity-based text retrieval". ACM Transactions on Internet Technology 10, n.º 1 (fevereiro de 2010): 1–39. http://dx.doi.org/10.1145/1667067.1667071.
Texto completo da fonteZhu, You-wen, Liu-sheng Huang, Dong Li e Wei Yang. "Privacy-preserving Text Information Hiding Detecting Algorithm". Journal of Electronics & Information Technology 33, n.º 2 (4 de março de 2011): 278–83. http://dx.doi.org/10.3724/sp.j.1146.2010.00375.
Texto completo da fonteTejaswini, G. "Cipher Text Policy Privacy Attribute-Based Security". International Journal of Reliable Information and Assurance 5, n.º 1 (30 de julho de 2017): 15–20. http://dx.doi.org/10.21742/ijria.2017.5.1.03.
Texto completo da fonteXiong, Xingxing, Shubo Liu, Dan Li, Jun Wang e Xiaoguang Niu. "Locally differentially private continuous location sharing with randomized response". International Journal of Distributed Sensor Networks 15, n.º 8 (agosto de 2019): 155014771987037. http://dx.doi.org/10.1177/1550147719870379.
Texto completo da fonteTeses / dissertações sobre o assunto "Text privacy"
Aryasomayajula, Naga Srinivasa Baradwaj. "Machine Learning Models for Categorizing Privacy Policy Text". University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535633397362514.
Texto completo da fonteHammoud, Khodor. "Trust in online data : privacy in text, and semantic-based author verification in micro-messages". Electronic Thesis or Diss., Université Paris Cité, 2021. http://www.theses.fr/2021UNIP5203.
Texto completo da fonteMany Problems surround the spread and use of data on social media. There is a need to promote trust on social platforms, regarding the sharing and consumption of data. Data online is mostly in textual form which poses challenges for automation solutions because of the richness of natural language. In addition, the use of micro-messages as the main means of communication on social media makes the problem much more challenging because of the scarceness of features to analyze per body of text. Our experiments show that data anonymity solutions cannot preserve user anonymity without sacrificing data quality. In addition, in the field of author verification, which is the problem of determining if a body of text was written by a specific person or not, given a set of documents known to be authored by them, we found a lack of research working with micro-messages. We also noticed that the state-of-the-art does not take text semantics into consideration, making them vulnerable to impersonation attacks. Motivated by these findings, we devote this thesis to tackle the tasks of (1) identifying the current problems with user data anonymity in text, and provide an initial novel semantic-based approach to tackle this problem, (2) study author verification in micro-messages and identify the challenges in this field, and develop a novel semantics-based approach to solve these challenges, and (3) study the effect of including semantics in handling manipulation attacks, and the temporal effect of data, where the authors might have changing opinions over time. The first part of the thesis focuses on user anonymity in textual data, with the aim to anonymize personal information from online user data for safe data analysis without compromising users’ privacy. We present an initial novel semantic-based approach, which can be customized to balance between preserving data quality and maximizing user anonymity depending on the application at hand. In the second part, we study author verification in micro-messages on social media. We confirm the lack of research in author verification on micro-messages, and we show that the state-of-the-art, which primarily handles long and medium-sized texts, does not perform well when applied on micro-messages. Then we present a semantics-based novel approach which uses word embeddings and sentiment analysis to collect the author’s opinion history to determine the correctness of the claim of authorship, and show its competitive performance on micro-messages. We use these results in the third part of the thesis to further improve upon our approach. We construct a dataset consisting of the tweets of the 88 most followed twitter influencers. We use it to show that the state-of-the-art is not able to handle impersonation attacks, where the content of a tweet is altered, changing the message behind the tweet, while the writing pattern is preserved. On the other hand, since our approach is aware of the text’s semantics, it is able to detect text manipulations with an accuracy above 90%. And in the fourth part of the thesis, we analyze the temporal effect of data on our approach for author verification. We study the change of authors’ opinions over time, and how to accommodate for that in our approach. We study trends of sentiments of an author per a specific topic over a period of time, and predict false authorship claims depending on what timeframe does the claim of authorship fall in
Connelly, Eric M. "[Redacted Text] and Surveillance: An Ideographic Analysis of the Struggle between National Security and Privacy". Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/communication_theses/66.
Texto completo da fonteRekanar, Kaavya. "Text Classification of Legitimate and Rogue online Privacy Policies : Manual Analysis and a Machine Learning Experimental Approach". Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13363.
Texto completo da fonteMysore, Gopinath Abhijith Athreya. "Automatic Detection of Section Title and Prose Text in HTML Documents Using Unsupervised and Supervised Learning". University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535371714338677.
Texto completo da fonteLiu, Meng-Chang. "Achieving privacy-preserving distributed statistical computation". Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/achieving-privacypreserving-distributed-statistical-computation(6831db5c-d605-4a38-9711-7592d2b94e01).html.
Texto completo da fonteSteiner, Wolfgang Ernst. "Justifying limitations on privacy: the influence of the proportionality test in South African and German law". Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/4738.
Texto completo da fonteBaldwin, Lind Paula. "Looking for privacy in Shakespeare : woman's place and space in a selection of plays and early modern texts". Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5848/.
Texto completo da fonteChow, Mark A. (Mark Andrew) 1972. "A rating system to test private investment decisions in public infrastructure projects". Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/50511.
Texto completo da fonteIncludes bibliographical references (p. 167-168).
This thesis will develop a basic method to evaluate the overall quality of proposed infrastructure projects for private sector financial investment. INFRATEST is meant to aid both potential private infrastructure developers and public entities, which desire to privatize certain infrastructure projects, in selection of the most appropriate infrastructure projects to benefit from the advantages of free enterprise. INFRATEST is premised on 15 equally-weighted factors which represent the major components that affect overall infrastructure project economic, financial, and technical viability. Associated with each of the 15 factors are indicators which measure the important aspects of their respective factors. There are 31 indicators in all and they are evaluated on a numerical scale of one to ten. Factor scores are determined from indicator value averages. INFRATEST can serve the private developer and the public entity by providing an information base for deciding which privately funded infrastructure development proposals deserve consideration in the capital markets and for deciding which proposed infrastructure projects are to be developed with public or private funds. Application of INFRATEST to two real-world project proposals, the SAVE project and the Northumberland Bridge project, demonstrated the method's ease and universality of application as well as the method's simple and clear conclusions.
by Mark A. Chow.
S.M.
Brodin, Gustav. "Privatekonomi i läroböcker : En läroboksstudie i samhällsvetenskap om privatekonomins kvantitet och innehåll". Thesis, Karlstads universitet, Institutionen för samhälls- och kulturvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-28147.
Texto completo da fonteThe debts of children and teenagers that are registered at the Swedish Enforcement Authority, have in the past few years hit an all-time high. School has a responsibility to try and stop this disturbing development. This essay is about private economy and its existence in three different textbooks for civics 1A1 and the Swedish high school. The goal is to investigate which support these books can give teachers and students. Private economy is a recent addition to the Swedish teaching program 2011 and is now read by all high school students. I have been able to identify the existence of private economy in textbooks by creating a code schedule. This way I have been able to decide the quantitative by simply counting words. The review is categorical in two parts where the second part illuminating the content and tries to make conclusions by different types of text analyses. The conclusion of this essay is that the books have its differences, both strengths and weaknesses. It is mostly the use of language that differs. A textbook in civics does not demand great text understanding. Two of the books handle this well, while the third one does not.
Livros sobre o assunto "Text privacy"
Aryeh Greenfield-A.G. Publications (Israel), ed. Protection of Privacy: Full text English translation of the Protection of Privacy Law 5741-1981 and of relevant subsidiary legislation correct as of November 1, 2011. 6a ed. Haifa, Israel]: Aryeh Greenfield-A.G. Publications, 2011.
Encontre o texto completo da fonteUnited States. Federal Aviation Administration., ed. Private pilot test guide. Renton, Wash: Aviation Supplies & Academics, 1992.
Encontre o texto completo da fonteBenson, Peter. Theory of private law: Selected topics and text. Toronto]: Faculty of Law, University of Toronto, 2013.
Encontre o texto completo da fonteUnited States. Health Care Financing Administration. Medicare and private health insurance: A training text. Baltimore, Maryland?]: U.S. Department of Health and Human Services, Health Care Financing Administration, 1985.
Encontre o texto completo da fonteBenson, Peter. Theory of private law: Selected topics and text. Toronto]: Faculty of Law, University of Toronto, 2014.
Encontre o texto completo da fonteBenson, Peter. Theory of private law: Selected topics and text. Toronto]: Faculty of Law, University of Toronto, 2010.
Encontre o texto completo da fonteUnited States. Federal Aviation Administration. Office of Flight Standards., ed. Private pilot: Practical test standards. Washington, DC: U.S. Dept. of Transportation, Federal Aviation Administration, Office of Flight Standards, 1987.
Encontre o texto completo da fonteUnited States. Federal Aviation Administration. Office of Flight Standards Service., ed. Private pilot: Practical test standards. Washington, DC: Flight Standards Service, 1995.
Encontre o texto completo da fonteUnited States. Federal Aviation Administration. Office of Flight Standards Service., ed. Private pilot: Practical test standards. Washington, DC: Flight Standards Service, 1995.
Encontre o texto completo da fonteMcCarthy, Steven J. Unbroken record: Electronic communication, forever undigitized. Falcon Heights, Minnesota]: Steven McCarthy, 2014.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Text privacy"
Salomon, David. "Data Hiding in Text". In Data Privacy and Security, 245–67. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21707-9_11.
Texto completo da fonteHart, Michael, Pratyusa Manadhata e Rob Johnson. "Text Classification for Data Loss Prevention". In Privacy Enhancing Technologies, 18–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22263-4_2.
Texto completo da fonteGarg, Vaibhav, L. Jean Camp, Katherine Connelly e Lesa Lorenzen-Huber. "Risk Communication Design: Video vs. Text". In Privacy Enhancing Technologies, 279–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31680-7_15.
Texto completo da fonteDanezis, George, Claudia Diaz, Carmela Troncoso e Ben Laurie. "$\text{Drac}$ : An Architecture for Anonymous Low-Volume Communications". In Privacy Enhancing Technologies, 202–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14527-8_12.
Texto completo da fonteMüller, Nicolas M., Daniel Kowatsch, Pascal Debus, Donika Mirdita e Konstantin Böttinger. "On GDPR Compliance of Companies’ Privacy Policies". In Text, Speech, and Dialogue, 151–59. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27947-9_13.
Texto completo da fonteHaralabopoulos, Giannis, Mercedes Torres Torres, Ioannis Anagnostopoulos e Derek McAuley. "Privacy-Preserving Text Labelling Through Crowdsourcing". In Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops, 431–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79157-5_35.
Texto completo da fonteManzanares-Salor, Benet, David Sánchez e Pierre Lison. "Automatic Evaluation of Disclosure Risks of Text Anonymization Methods". In Privacy in Statistical Databases, 157–71. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13945-1_12.
Texto completo da fonteDalianis, Hercules. "Ethics and Privacy of Patient Records for Clinical Text Mining Research". In Clinical Text Mining, 97–108. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78503-5_9.
Texto completo da fonteFernandes, Natasha, Mark Dras e Annabelle McIver. "Generalised Differential Privacy for Text Document Processing". In Lecture Notes in Computer Science, 123–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17138-4_6.
Texto completo da fonteAlnasser, Walaa, Ghazaleh Beigi e Huan Liu. "Privacy Preserving Text Representation Learning Using BERT". In Social, Cultural, and Behavioral Modeling, 91–100. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80387-2_9.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Text privacy"
Xu, Qiongkai, Lizhen Qu, Chenchen Xu e Ran Cui. "Privacy-Aware Text Rewriting". In Proceedings of the 12th International Conference on Natural Language Generation. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-8633.
Texto completo da fontePonomareva, Natalia, Jasmijn Bastings e Sergei Vassilvitskii. "Training Text-to-Text Transformers with Privacy Guarantees". In Proceedings of the Fourth Workshop on Privacy in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.privatenlp-1.4.
Texto completo da fontePonomareva, Natalia, Jasmijn Bastings e Sergei Vassilvitskii. "Training Text-to-Text Transformers with Privacy Guarantees". In Findings of the Association for Computational Linguistics: ACL 2022. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.findings-acl.171.
Texto completo da fonteBeigi, Ghazaleh, Kai Shu, Ruocheng Guo, Suhang Wang e Huan Liu. "Privacy Preserving Text Representation Learning". In HT '19: 30th ACM Conference on Hypertext and Social Media. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3342220.3344925.
Texto completo da fonteYue, Xiang, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun e Sherman S. M. Chow. "Differential Privacy for Text Analytics via Natural Text Sanitization". In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.findings-acl.337.
Texto completo da fonteCoavoux, Maximin, Shashi Narayan e Shay B. Cohen. "Privacy-preserving Neural Representations of Text". In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/d18-1001.
Texto completo da fonteBasu, Priyam, Tiasa Singha Roy, Rakshit Naidu e Zumrut Muftuoglu. "Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning". In Proceedings of the Third Workshop on Economics and Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.econlp-1.7.
Texto completo da fonteLi, Yitong, Timothy Baldwin e Trevor Cohn. "Towards Robust and Privacy-preserving Text Representations". In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/p18-2005.
Texto completo da fonteAdelani, David Ifeoluwa, Ali Davody, Thomas Kleinbauer e Dietrich Klakow. "Privacy Guarantees for De-Identifying Text Transformations". In Interspeech 2020. ISCA: ISCA, 2020. http://dx.doi.org/10.21437/interspeech.2020-2208.
Texto completo da fonteCostantino, Gianpiero, Antonio La Marra, Fabio Martinelli, Andrea Saracino e Mina Sheikhalishahi. "Privacy-preserving text mining as a service". In 2017 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2017. http://dx.doi.org/10.1109/iscc.2017.8024639.
Texto completo da fonteRelatórios de organizações sobre o assunto "Text privacy"
Cantor, Amy G., Rebecca M. Jungbauer, Andrea C. Skelly, Erica L. Hart, Katherine Jorda, Cynthia Davis-O'Reilly, Aaron B. Caughey e Ellen L. Tilden. Respectful Maternity Care: Dissemination and Implementation of Perinatal Safety Culture To Improve Equitable Maternal Healthcare Delivery and Outcomes. Agency for Healthcare Research and Quality (AHRQ), janeiro de 2024. http://dx.doi.org/10.23970/ahrqepccer269.
Texto completo da fonteAndrabi, Tahir, Natalie Bau, Jishnu Das e Asim I. Khwaja. Heterogeneity in School Value-Added and the Private Premium. Research on Improving Systems of Education (RISE), novembro de 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/116.
Texto completo da fonteAgüero, Jorge M., e Verónica Frisancho. Systematic Bias in Sensitive Health Behaviors and Its Impact on Treatment Effects: An Application to Violence against Women. Inter-American Development Bank, abril de 2017. http://dx.doi.org/10.18235/0007031.
Texto completo da fonteAndrabi, Tahir, Natalie Bau, Jishnu Das, Naureen Karachiwalla e Asim I. Khwaja. Crowding in Private Quality: The Equilibrium Effects of Public Spending in Education. Research on Improving Systems of Education (RISE), janeiro de 2023. http://dx.doi.org/10.35489/bsg-rise-wp_2023/124.
Texto completo da fonteBonaldi, Pietro, e Mauricio Villamizar-Villegas. An Auction-Based Test of Private Information in an Interdealer FX Market. Bogotá, Colombia: Banco de la República, agosto de 2018. http://dx.doi.org/10.32468/be.1049.
Texto completo da fonteBronnenberg, Bart, Jean-Pierre Dubé e Robert Sanders. Consumer Misinformation and the Brand Premium: A Private Label Blind Taste Test. Cambridge, MA: National Bureau of Economic Research, novembro de 2018. http://dx.doi.org/10.3386/w25214.
Texto completo da fonteAhwireng-Obeng, Asabea Shirley, e Frederick Ahwireng-Obeng. Private Philanthropic Cross-Border Flows and Sustainable Development in Africa. Centre on African Philanthropy and Social Investment, agosto de 2011. http://dx.doi.org/10.47019/2021.ra1.
Texto completo da fonteGan, Li, Feng Huang e Adalbert Mayer. A Simple Test of Private Information in the Insurance Markets with Heterogeneous Insurance Demand. Cambridge, MA: National Bureau of Economic Research, janeiro de 2011. http://dx.doi.org/10.3386/w16738.
Texto completo da fonteBorger, Michael, Gregory Elacqua, Isabel Jacas, Christopher Neilson e Anne Sofie Westh Olsen. Report Cards: Parental Preferences, Information and School Choice in Haiti. Inter-American Development Bank, maio de 2023. http://dx.doi.org/10.18235/0004933.
Texto completo da fonteMoreno, Ángel Iván, e Teresa Caminero. Assessing the data challenges of climate-related disclosures in european banks. A text mining study. Madrid: Banco de España, setembro de 2023. http://dx.doi.org/10.53479/33752.
Texto completo da fonte