Littérature scientifique sur le sujet « Emerging trend detection »
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Articles de revues sur le sujet "Emerging trend detection"
Hsu, Ming-Hung, Yu-Hui Chang et Hsin-Hsi Chen. « Temporal Correlation between Social Tags and Emerging Long-Term Trend Detection ». Proceedings of the International AAAI Conference on Web and Social Media 4, no 1 (16 mai 2010) : 255–58. http://dx.doi.org/10.1609/icwsm.v4i1.14049.
Texte intégralVALENCIA, MARIA, CODRINA LAUTH et ERNESTINA MENASALVAS. « EMERGING USER INTENTIONS : MATCHING USER QUERIES WITH TOPIC EVOLUTION IN NEWS TEXT STREAMS ». International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 17, supp01 (août 2009) : 59–80. http://dx.doi.org/10.1142/s0218488509006030.
Texte intégralLackner, Bettina C., Andrea K. Steiner, Gabriele C. Hegerl et Gottfried Kirchengast. « Atmospheric Climate Change Detection by Radio Occultation Data Using a Fingerprinting Method ». Journal of Climate 24, no 20 (15 octobre 2011) : 5275–91. http://dx.doi.org/10.1175/2011jcli3966.1.
Texte intégralWu, Yuqi, Yuhan Deng, Longgang Zhang, Qidong Zhang et Ran Bao. « Research on the Development of Unmanned Underwater System Detection Technology ». Journal of Physics : Conference Series 2218, no 1 (1 mars 2022) : 012079. http://dx.doi.org/10.1088/1742-6596/2218/1/012079.
Texte intégralSUCHIT K. RAI, SUNIL KUMAR et MANOJ CHAUDHARY. « Detection of annual and seasonal temperature variability and change using non-parametric test- A case study of Bundelkhand region of central India ». Journal of Agrometeorology 23, no 4 (11 novembre 2021) : 402–8. http://dx.doi.org/10.54386/jam.v23i4.144.
Texte intégralParlina, Anne, Kalamullah Ramli et Hendri Murfi. « Exposing Emerging Trends in Smart Sustainable City Research Using Deep Autoencoders-Based Fuzzy C-Means ». Sustainability 13, no 5 (7 mars 2021) : 2876. http://dx.doi.org/10.3390/su13052876.
Texte intégralPerisic, Marija Majda, Mario Štorga et John S. Gero. « COMPUTATIONAL STUDY ON DESIGN SPACE EXPANSION DURING TEAMWORK ». Proceedings of the Design Society 1 (27 juillet 2021) : 691–700. http://dx.doi.org/10.1017/pds.2021.69.
Texte intégralSalunkhe, Uma R., et Suresh N. Mali. « Security Enrichment in Intrusion Detection System Using Classifier Ensemble ». Journal of Electrical and Computer Engineering 2017 (2017) : 1–6. http://dx.doi.org/10.1155/2017/1794849.
Texte intégralKatsurai, Marie, et Shunsuke Ono. « TrendNets : mapping emerging research trends from dynamic co-word networks via sparse representation ». Scientometrics 121, no 3 (18 octobre 2019) : 1583–98. http://dx.doi.org/10.1007/s11192-019-03241-6.
Texte intégralSchaffhauser, Andreas, Wojciech Mazurczyk, Luca Caviglione, Marco Zuppelli et Julio Hernandez-Castro. « Efficient Detection and Recovery of Malicious PowerShell Scripts Embedded into Digital Images ». Security and Communication Networks 2022 (29 juin 2022) : 1–12. http://dx.doi.org/10.1155/2022/4477317.
Texte intégralThèses sur le sujet "Emerging trend detection"
Nguyen, Nhu Khoa. « Emerging Trend Detection in News Articles ». Electronic Thesis or Diss., La Rochelle, 2023. http://www.theses.fr/2023LAROS003.
Texte intégralIn the financial domain, information plays an utmost important role in making investment/business decisions as good knowledge can lead to crafting correct approaches in how to invest or if the investment is worth it. Moreover, being able to identify potential emerging themes/topics is an integral part of this field, since it can help get a head start over other investors, thus gaining a huge competitive advantage. To deduce topics that can be emerging in the future, data such as annual financial reports, stock market, and management meeting summaries are usually considered for review by professional financial experts. Reliable sources of information coming from reputable news publishers, can also be utilized for the purpose of detecting emerging themes. Unlike social media, articles from these publishers have high credibility and quality, thus when analyzed in large sums, it is likely to discover dormant/hidden information about trends or what can become future trends. However, due to the vast amount of information generated each day, it has become more demanding and difficult to analyze the data manually for the purpose of trend identification. Our research explores and analyzes data from different quality sources, such as scientific publication abstracts and a provided news article dataset from Bloomberg called Event-Driven Feed (EDF) to experiment on Emerging Trend Detection. Due to the enormous amount of available data spread over extended time periods, it encourages the use of contrastive approaches to measuring the divergence between past and present surrounding context of extracted words and phrases, thus comparing the similarity between unique vector representations of each interval to discover movement in word usage that can lead to the discovery of new trend. Experimental results reveal that the assessment of context change through time of selected terms is able to detect critical emerging trends and points of emergence. It is also discovered that assessing the evolution of context over a long time span is better than just contrasting the two most recent points in time
Redyuk, Sergey. « Finding early signals of emerging trends in text through topic modeling and anomaly detection ». Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15507.
Texte intégralPetit, Eva. « Modélisation de données de surveillance épidémiologique de la faune sauvage en vue de la détection de problèmes sanitaires inhabituels ». Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENS006/document.
Texte intégralRecent studies have shown that amongst emerging infectious disease events in humans, about 40% were zoonoses linked to wildlife. Disease surveillance of wildlife should help to improve health protection of these animals and also of domestic animals and humans that are exposed to these pathogenic agents. Our aim was to develop tools capable of detecting unusual disease events in free ranging wildlife, by adopting a syndromic approach, as it is used for human health surveillance, with pathological profiles as early unspecific health indicators. We used the information registered by a national network monitoring causes of death in wildlife in France since 1986, called SAGIR. More than 50.000 cases of mortality in wildlife were recorded up to 2007, representing 244 species of terrestrial mammals and birds, and were attributed to 220 different causes of death. The network was first evaluated for its capacity to detect early unusual events. Syndromic classes were then defined by a statistical typology of the lesions observed on the carcasses. Syndrome time series were analyzed, using two complimentary methods of detection, one robust detection algorithm developed by Farrington and another generalized linear model with periodic terms. Historical trends of occurrence of these syndromes and greater-than-expected counts (signals) were identified. Reporting of unusual mortality events in the network bulletin was used to interpret these signals. The study analyses the relevance of the use of syndromic surveillance on this type of data and gives elements for future improvements
Junior, José Sergio Bleckmann Reis. « Métodos e softwares para análise da produção científica e detecção de frentes emergentes de pesquisa ». Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/85/85133/tde-14102016-131850/.
Texte intégralThe progress of previous projects pointed out the need to face some problems of software for detecting emerging research and development trends from databases of scientific publications. It became evident the lack of efficient computing applications dedicated to this purpose that are artifacts of great usefulness to better planning research and development programs in institutions. A review of the currently available software was performed, in order to clearly delineate the opportunity to develop new tools. As a result, a software called Citesnake was implemented, designed particularly to help the detection and study of emerging trends from the analysis of networks of several types extracted from the scientific databases. Using this robust and effective computational tool, analyzes of emerging research and development trends were performed in the field of Generation IV Nuclear Power Generation Systems, in such a way to point out, among the most promising reactor types selected by the GIF - Generation IV International Forum, those that have better evolved over the past ten years and seem to be currently the most capable of fulfilling the promises made on their innovative concepts.
Decker, Sheron Levar. « Detection of bursty and emerging trends towards identification of researchers at the early stage of trends ». 2007. http://purl.galileo.usg.edu/uga%5Fetd/decker%5Fsheron%5Fl%5F200708%5Fms.
Texte intégralLivres sur le sujet "Emerging trend detection"
Freedman, Jeri. Lymphoma : Current and emerging trends in detection and treatment. New York : Rosen Pub. Group, 2006.
Trouver le texte intégralFreedman, Jeri. Brain cancer : Current and emerging trends in detection and treatment. New York : Rosen, 2008.
Trouver le texte intégralEsophageal cancer : Current and emerging trends in detection and treatment. New York : Rosen Pub., 2012.
Trouver le texte intégralCasil, Amy Sterling. Pancreatic cancer : Current and emerging trends in detection and treatment. New York : Rosen Pub., 2008.
Trouver le texte intégralFreedman, Jeri. Ovarian cancer : Current and emerging trends in detection and treatment. New York : Rosen Pub. Group, 2009.
Trouver le texte intégralHussain, Chaudhery. Smartphone-Based Detection Devices : Emerging Trends in Analytical Techniques. Elsevier, 2021.
Trouver le texte intégralHussain, Chaudhery Mustansar. Smartphone-Based Detection Devices : Emerging Trends in Analytical Techniques. Elsevier, 2021.
Trouver le texte intégralHarmon, Daniel E. Leukemia Current and Emerging Trends in Detection and Treatment. Rosen Publishing Group, 2011.
Trouver le texte intégralHasan, Heather. Testicular Cancer Current and Emerging Trends in Detection and Treatment. Rosen Publishing Group, 2011.
Trouver le texte intégralBreast Cancer : Current and Emerging Trends in Detection and Treatment. Rosen Publishing Group, 2005.
Trouver le texte intégralChapitres de livres sur le sujet "Emerging trend detection"
Kontostathis, April, Leon M. Galitsky, William M. Pottenger, Soma Roy et Daniel J. Phelps. « A Survey of Emerging Trend Detection in Textual Data Mining ». Dans Survey of Text Mining, 185–224. New York, NY : Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4305-0_9.
Texte intégralThomas Rincy, N., et Roopam Gupta. « A Survey of Network Intrusion Detection Using Machine Learning Techniques ». Dans Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics, 81–122. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66288-2_4.
Texte intégralPatra, Santanu, Rashmi Madhuri et Prashant K. Sharma. « Role of Nanomaterials as an Emerging Trend Towards the Detection of Winged Contaminants ». Dans Nanotechnology in Oil and Gas Industries, 245–89. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60630-9_9.
Texte intégralPopoola, Segun I., Ruth Ande, Kassim B. Fatai et Bamidele Adebisi. « Deep Bidirectional Gated Recurrent Unit for Botnet Detection in Smart Homes ». Dans Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics, 29–55. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66288-2_2.
Texte intégralThomas Rincy, N., et Roopam Gupta. « Correction to : A Survey of Network Intrusion Detection Using Machine Learning Techniques ». Dans Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics, C1. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66288-2_13.
Texte intégralAdewole, Kayode S., Muiz O. Raheem, Oluwakemi C. Abikoye, Adeleke R. Ajiboye, Tinuke O. Oladele, Muhammed K. Jimoh et Dayo R. Aremu. « Malicious Uniform Resource Locator Detection Using Wolf Optimization Algorithm and Random Forest Classifier ». Dans Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics, 177–96. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66288-2_7.
Texte intégralZeng, Li, Yang Li et Zili Li. « Research Hotspots, Emerging Trend and Front of Fraud Detection Research : A Scientometric Analysis (1984–2021) ». Dans Data Mining and Big Data, 91–102. Singapore : Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8991-9_8.
Texte intégralKhan, Summaiyya, Akrema, Rizwan Arif, Shama Yasmeen et Rahisuddin. « Recent Advancement in Nanostructured-Based Electrochemical Genosensors for Pathogen Detection ». Dans Emerging Trends in Nanotechnology, 339–58. Singapore : Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9904-0_12.
Texte intégralSuresh, S., M. Mohan, C. Thyagarajan et R. Kedar. « Detection of Ransomware in Emails Through Anomaly Based Detection ». Dans Emerging Trends in Computing and Expert Technology, 604–13. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32150-5_59.
Texte intégralDash, Rajesh Kumar, Manojit Samanta et Debi Prasanna Kanungo. « Debris Flow Hazard in India : Current Status, Research Trends, and Emerging Challenges ». Dans Landslides : Detection, Prediction and Monitoring, 211–31. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-23859-8_10.
Texte intégralActes de conférences sur le sujet "Emerging trend detection"
Nguyen, Nhu Khoa, Emanuela Boros, Gaël Lejeune, Antoine Doucet et Thierry Delahaut. « Utilizing Keywords Evolution in Context for Emerging Trend Detection in Scientific Publications ». Dans SoICT 2022 : The 11th International Symposium on Information and Communication Technology. New York, NY, USA : ACM, 2022. http://dx.doi.org/10.1145/3568562.3568640.
Texte intégralAmeerali, Aaron, Nadine Sangster et Gerard Ragbir. « AUTONOMOUS DETECTION OF VEHICULAR WHEEL ALIGNMENT PARAMETERS ». Dans International Conference on Emerging Trends in Engineering & Technology (IConETech-2020). Faculty of Engineering, The University of the West Indies, St. Augustine, 2020. http://dx.doi.org/10.47412/boqw8777.
Texte intégralAkasaki, Satoshi, Naoki Yoshinaga et Masashi Toyoda. « Early Discovery of Emerging Entities in Microblogs ». Dans Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California : International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/678.
Texte intégralTucker, Conrad S., et Harrison M. Kim. « Trending Mining for Predictive Product Design ». Dans ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28364.
Texte intégralHuang, Jihua, et Han-Shue Tan. « Cooperative Collision Detection Based on Future-Trajectory Prediction ». Dans ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14543.
Texte intégralBrennan, Feargal, et Bart de Leeuw. « The Use of Inspection and Monitoring Reliability Information in Criticality and Defect Assessments of Ship and Offshore Structures ». Dans ASME 2008 27th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/omae2008-57934.
Texte intégralSledge, Isaac J., James M. Keller et Gregory L. Alexander. « Emergent trend detection in diurnal activity ». Dans 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4650040.
Texte intégralZoveidavianpoor, Mansoor, Eadie Azahar Rosland, Pasi Laakkonen, Saman Aryana, Mohd Zaidi Jaafar, Jamal Mohamad Ibrahim, Hoshang Kolivand et al. « The Concept of Need for a Downhole Scale Inspection Tool : An Appraisal for an Emerging Technology in Scale Management ». Dans International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21265-ms.
Texte intégralUgoyah, Joy, et Anita Mary Igbine. « Applications of AI and Data-Driven Modeling in Energy Production and Marketing Processes ». Dans SPE Nigeria Annual International Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/207153-ms.
Texte intégralLiu, Zhiming, et Xiangyu Liu. « Future design outlook of wearable devices ». Dans 10th International Conference on Human Interaction and Emerging Technologies (IHIET 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004053.
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