Relevant bibliographies by topics / Message prediction

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Message prediction'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Message prediction"

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Short, Kevin M. "Signal Extraction from Chaotic Communications." International Journal of Bifurcation and Chaos 07, no. 07 (1997): 1579–97. http://dx.doi.org/10.1142/s0218127497001230.

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This paper will consider the use of nonlinear dynamic (NLD) forecasting to extract messages from chaotic communication systems. Earlier work has shown that one-step prediction methods have sometimes been able to reveal the presence of hidden messages as well as the frequency content of the hidden messages. However, recovery of the actual hidden message usually involved filtering in the frequency domain. In this paper we show that it may be possible to extract the hidden message signal without filtering in the frequency domain. The approaches which will be discussed involve either the use of mu
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Iwamoto, Yoshiyuki, Koichi Suga, Kanemitsu Ootsu, Takashi Yokota, and Takanobu Baba. "Receiving message prediction method." Parallel Computing 29, no. 11-12 (2003): 1509–38. http://dx.doi.org/10.1016/j.parco.2003.05.005.

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Huang, Boning, and Junkang Wei. "Research on Deep Learning-Based Financial Risk Prediction." Scientific Programming 2021 (December 13, 2021): 1–8. http://dx.doi.org/10.1155/2021/6913427.

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Financial text-based risk prediction is an important subset for financial analysis. Through automatic analysis of public financial comments, fundamentals on current financial expectations can be evaluated. A deep learning method for financial risk prediction based on sentiment classification is proposed in this paper. The proposed method consists of two steps. Firstly, the abstract of the financial message is extracted according to the seq2seq model. During the extraction process, the seq2seq model can cope with the situation of different input message lengths. After the abstraction, invalid i
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Laddha, Abhishek, Mohamed Hanoosh, Debdoot Mukherjee, Parth Patwa, and Ankur Narang. "Understanding Chat Messages for Sticker Recommendation in Messaging Apps." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 08 (2020): 13156–63. http://dx.doi.org/10.1609/aaai.v34i08.7019.

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Stickers are popularly used in messaging apps such as Hike to visually express a nuanced range of thoughts and utterances to convey exaggerated emotions. However, discovering the right sticker from a large and ever expanding pool of stickers while chatting can be cumbersome. In this paper, we describe a system for recommending stickers in real time as the user is typing based on the context of the conversation. We decompose the sticker recommendation (SR) problem into two steps. First, we predict the message that the user is likely to send in the chat. Second, we substitute the predicted messa
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Osipenko, Sergey, Eugene Nikolaev, and Yury Kostyukevich. "Retention Time Prediction with Message-Passing Neural Networks." Separations 9, no. 10 (2022): 291. http://dx.doi.org/10.3390/separations9100291.

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Retention time prediction, facilitated by advances in machine learning, has become a useful tool in untargeted LC-MS applications. State-of-the-art approaches include graph neural networks and 1D-convolutional neural networks that are trained on the METLIN small molecule retention time dataset (SMRT). These approaches demonstrate accurate predictions comparable with the experimental error for the training set. The weak point of retention time prediction approaches is the transfer of predictions to various systems. The accuracy of this step depends both on the method of mapping and on the accur
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Mahendrakar, Nikhil Anand. "Next Message Prediction in a Sequence using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 10 (2022): 152–55. http://dx.doi.org/10.22214/ijraset.2022.46959.

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Abstract: Prediction of next message after given a sequence of messages has lot of applications. It has applications in NLP (natural language processing), Log Anomaly Detection, Automating Customer Service and many more. Automating Customer Service is one such application which shall be in great focus in this paper. For any organization, automating customer service can save a lot of revenue and time. It increases the response time for customers/users, which in turn increases customer satisfaction. It reduces the load on the business. In this paper, we use machine learning algorithm (Support ve
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Yeh, Yi Hsuah, Yuan Cheng Lai, Jian Wei Lin, Ching Neng Lai, and Hui Chuan Weng. "A Tracking System with Location-Based Delivering for Reducing Short Message Transmissions." Applied Mechanics and Materials 284-287 (January 2013): 2682–86. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2682.

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Combining Short Message Service (SMS) and Global Position System (GPS), this paper proposes a novel method, called Location-based Delivering (LBD), and further develops a realistic system to tracking target's moving. LBD can reduce the number of short message transmissions while maintaining location accuracy within an acceptable range. LBD mainly adopts two proposed techniques: location prediction and dynamic threshold. Location prediction utilizes the current target's location, moving speed, bearing to predict its next location. When the distance between the predicted location and the actual
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Geschke, Daniel, Kai Sassenberg, Georg Ruhrmann, and Denise Sommer. "Behavior Speaks Louder than Traits." Zeitschrift für Psychologie / Journal of Psychology 215, no. 4 (2007): 248–54. http://dx.doi.org/10.1027/0044-3409.215.4.248.

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The impact of message abstractness on recipients is controversial. Research on person perception suggests that abstract messages are more influential, whereas research on communication and its outcomes suggests that concrete, vivid communication has greater impact. It was predicted that the latter also applies to the domain of person perception if the message contains unexpected (i.e., stereotype inconsistent) information. This prediction was tested experimentally. It was found that a message about a target person with unexpected content exerts more influence when it is concrete than when it i
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Kim, Hyun Suk, Sijia Yang, Minji Kim, Brett Hemenway, Lyle Ungar, and Joseph N. Cappella. "An Experimental Study of Recommendation Algorithms for Tailored Health Communication." Computational Communication Research 1, no. 1 (2019): 103–29. http://dx.doi.org/10.5117/ccr2019.1.005.sukk.

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Abstract Recommendation algorithms are widely used in online cultural markets to provide personalized suggestions for products like books and movies. At the heart of the commercial success of recommendation algorithms is their ability to make an accurate prediction of a target person’s preferences for previously unseen items. Can these algorithms also be used to predict which health messages an individual will evaluate favorably, and thereby provide effective tailored communication to the person? Although there is evidence that message tailoring enhances persuasion, little research has examine
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Zhang, Cui, Wang, Ding, and Xia. "Distributed Joint Cooperative Self-Localization and Target Tracking Algorithm for Mobile Networks." Sensors 19, no. 18 (2019): 3829. http://dx.doi.org/10.3390/s19183829.

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: Location information is a key issue for applications of the Internet of Things. In this paper, we focus on mobile wireless networks with moving agents and targets. The positioning process is divided into two phases based on the factor graph, i.e., a prediction phase and a joint self-location and tracking phase. In the prediction phase, we develop an adaptive prediction model by exploiting the correlation of trajectories within a short period to formulate the prediction message. In the joint positioning phase, agents calculate the cooperative messages according to variational message passing
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Dissertations / Theses on the topic "Message prediction"

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Bangalore, Narendranath Rao Amith Kaushal. "Online Message Delay Prediction for Model Predictive Control over Controller Area Network." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78626.

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Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive
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Swanson, Kyle(Kyle W. ). "Message passing neural networks for molecular property prediction." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123133.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 81-84).<br>Developing new drugs relies heavily on understanding the various molecular properties of potential drug candidates. While experimental assays performed in the lab are the best sou
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Chew, Zhen Bob. "Modelling message-oriented-middleware brokers using autoregressive models for bottleneck prediction." Thesis, Queen Mary, University of London, 2013. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8832.

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Message brokers are the backbone of modern publish subscribe messaging systems. These brokers can degrade or fail for a variety of reasons. This research specifically looks at the detection, prediction and mitigation of bottlenecks in brokers. The message-oriented-middleware framework here uses either a cluster of brokers on a Local Area Network (LAN) or a federation of brokers on a Wide Area Network (WAN) to route messages, facilitate multicasting and ameliorate demand surges and geographically related faults. Sensors have been constructed to monitor brokers and controllers to run the bottlen
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Panadero, Javier. "Predicción del rendimiento: Análisis de la escalabilidad de aplicaciones paralelas." Doctoral thesis, Universitat Autònoma de Barcelona, 2015. http://hdl.handle.net/10803/310211.

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Executar aplicacions paral·leles de pas de missatges sobre un elevat nombre de recursos de manera eficient no és una tasca trivial. A causa de la complexa interacció entre l'aplicació paral·lela i el sistema HPC, a mesura que s'augmenta el nombre de processos de l'aplicació, depenent del sistema, pot arribar un punt on l'aplicació presenti el seu límit d'escalabilitat, moment a partir del qual es començaran a produir ineficiències en el sistema, comportant a un ús ineficient del mateix. Aquest problema es torna e
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Ramaccia, Julie Brady. "What am I Eating? The Use of Health and Environmental Messages in Predicting a Sustainable Diet." University of Dayton / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1304384504.

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Sahin, Serdar. "Advanced receivers for distributed cooperation in mobile ad hoc networks." Thesis, Toulouse, INPT, 2019. http://www.theses.fr/2019INPT0089.

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Les réseaux ad hoc mobiles (MANETs) sont des systèmes de communication sans fil rapidement déployables et qui fonctionnent avec une coordination minimale, ceci afin d'éviter les pertes d'efficacité spectrale induites par la signalisation. Les stratégies de transmissions coopératives présentent un intérêt pour les MANETs, mais la nature distribuée de tels protocoles peut augmenter le niveau d'interférence avec un impact autant plus sévère que l'on cherche à pousser les limites des efficacités énergétique et spectrale. L'impact de l'interférence doit alors être réduit par l'utilisation d'algorit
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Nitz, Michael Earl. "Involvement as a predictor of behavioral response to disease prevention and control messages: A multi-dimensional approach." Diss., The University of Arizona, 1995. http://hdl.handle.net/10150/187156.

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One of the fundamental problems in health campaign research is obtaining behavioral compliance. This dissertation proposed a multi-dimensional framework of involvement to help address this dilemma. Johnson and Eagly's tripartite framework of involvement was used. Involvement was comprised of outcome-relevance, value-relevance, and impression-relevance. Surveys were conducted using the topic of skin cancer. Results indicated that involvement significantly enhanced subjects' intention to comply, knowledge levels, and media usage. Demographic analyses revealed that gender and education, as well a
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Harben, Beth Kwon Wi-Suk Forsythe Sandra Monk. "Predicting consumers' cause-brand alliance attitude and purchase intention the influence of cause involvement, message source, perceived motivations, and cause-brand fit /." Auburn, Ala, 2009. http://hdl.handle.net/10415/1890.

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Amor, Yasmine. "Ιntelligent apprοach fοr trafic cοngestiοn predictiοn". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMR129.

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La congestion routière constitue un défi majeur pour les zones urbaines, car le volume de véhicules continue de croître plus rapidement que la capacité globale du réseau routier. Cette croissance a des répercussions sur l'activité économique, la durabilité environnementale et la qualité de vie. Bien que des stratégies visant à atténuer la congestion routière ont connu des améliorations au cours des dernières décennies, de nombreux pays ont encore du mal à la gérer efficacement.Divers modèles ont été développés pour aborder ce problème. Cependant, les approches existantes peinent souvent à four
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Thomas, Sarah Nichole. "Making the Transition: Comparing the Use of Narrative and Non-Narrative Messages to Increase Fruit and Vegetable Intake in Cancer Survivors." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1460993101.

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Books on the topic "Message prediction"

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Nagle, Frederick W. A description of prediction errors associated with the T-Bus-4 navigation message and a corrective procedure. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1986.

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Cossever, Daniel. Message prediction for an icon-based pediatric communication aid. 2005.

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Eshetu, Getnet. Complimentary Effects of Integrative Behavioral Prediction and Media Priming for Message Delivery in Changing Hand Washing Behavior of Primary Sch. GRIN Verlag GmbH, 2013.

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Max, Heindel, and Augusta Foss Heindel. The Message of the Stars: An Esoteric Exposition of Medical and Natal Astrology Explaining the Arts of Prediction and Diagnosis of Disease,. Franklin Classics, 2018.

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Max, Heindel, and Augusta Foss Heindel. The Message of the Stars: An Esoteric Exposition of Medical and Natal Astrology Explaining the Arts of Prediction and Diagnosis of Disease,. Franklin Classics Trade Press, 2018.

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Max, Heindel, and Augusta Foss Heindel. The Message of the Stars: An Esoteric Exposition of Medical and Natal Astrology Explaining the Arts of Prediction and Diagnosis of Disease,. Franklin Classics Trade Press, 2018.

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Guestbooks, Sassy. 4th Birthday Guestbook: Circus Themed - Fourth Party Children Toddler Event Celebration Keepsake Book - Family Friend Sign in Write Name, Advice Wish Message Comment Prediction - W/ Gift Recorder Tracker Log and Picture Space. Independently Published, 2019.

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Occasions, Treasured. 5th Birthday Guestbook: Circus Themed - Fifth Party Children Toddler Event Celebration Keepsake Book - Family Friend Sign in Write Name, Advice Wish Message Comment Prediction - W/ Gift Recorder Tracker Log and Picture Space. Independently Published, 2019.

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Gurus, The Guest Book. 5th Birthday Guestbook: Tropical Fruit Themed - Fifth Party Children Toddler Event Celebration Keepsake Book - Family Friend Sign in Write Name, Advice Wish Message Comment Prediction - W/ Gift Recorder Tracker Log and Picture Space. Independently Published, 2019.

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3rd Birthday Guestbook: Pastel Balloons Themed - Third Party Baby Anniversary Event Celebration Keepsake Book - Family Friend Sign in Write Name, Advice Wish Message Comment Prediction - W/ Gift Recorder Tracker Log and Picture Space. Independently Published, 2019.

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Book chapters on the topic "Message prediction"

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Afsahi, Ahmad, and Nikitas J. Dimopoulos. "Communication Prediction in Message-Passing Multiprocessors." In The Kluwer International Series in Engineering and Computer Science. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0849-6_18.

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Baba, Takanobu, Takashi Yokota, Kanemitsu Ootsu, Fumihito Furukawa, and Yoshiyuki Iwamoto. "Receiving-Message Prediction and its Speculative Execution." In High-Performance Computing. John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0471732710.ch13.

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Makalic, Enes, and Daniel F. Schmidt. "Minimum Message Length Analysis of the Behrens–Fisher Problem." In Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-44958-1_19.

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Abdalhaq, B., G. Bianchini, A. Cortés, T. Margalef, and E. Luque. "Improving Wildland Fire Prediction on MPI Clusters." In Recent Advances in Parallel Virtual Machine and Message Passing Interface. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39924-7_69.

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Afsahi, Ahmad, and Nikitas J. Dimopoulos. "Efficient Communication Using Message Prediction for Cluster of Multiprocessors." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10720115_12.

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Chiorrini, Andrea, Claudia Diamantini, Alex Mircoli, and Domenico Potena. "Exploiting Instance Graphs and Graph Neural Networks for Next Activity Prediction." In Lecture Notes in Business Information Processing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98581-3_9.

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AbstractNowadays, a lot of data regarding business process executions are maintained in event logs. The next activity prediction task exploits such event logs to predict how process executions will unfold up until their completion. The present paper proposes a new approach to address this task: instead of using traces to perform predictions, we propose to use the instance graphs derived from traces. To make the most out of such representation we train a message passing neural network, specifically a Deep Graph Convolutional Neural Network to predict the next activity that will be performed in
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Jiang, Bo, Jiguang Liang, Ying Sha, et al. "Unifying User and Message Clustering Information for Retweeting Behavior Prediction." In Web-Age Information Management. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39958-4_23.

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Schmidt, Daniel F. "Minimum Message Length Order Selection and Parameter Estimation of Moving Average Models." In Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-44958-1_26.

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Denham, Mónica, Ana Cortés, and Tomás Margalef. "Parallel Dynamic Data Driven Genetic Algorithm for Forest Fire Prediction." In Recent Advances in Parallel Virtual Machine and Message Passing Interface. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03770-2_40.

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Mancini, E., M. Rak, R. Torella, and U. Villano. "Off-Line Performance Prediction of Message-Passing Applications on Cluster Systems." In Recent Advances in Parallel Virtual Machine and Message Passing Interface. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39924-7_11.

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Conference papers on the topic "Message prediction"

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Liu, Bingyi, Xun Shao, Haoxiang Zhao, Enshu Wang, and Zhi Liu. "CPIMAC: MEC-assisted Message Dissemination Based on Traffic Prediction at Intersections." In 2024 IEEE Smart World Congress (SWC). IEEE, 2024. https://doi.org/10.1109/swc62898.2024.00099.

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Sinha, Ashutosh Kr, Lov Kumar, and Vikram Singh. "Exploring Meta-Embeddings in Ensemble and Deep Learning for Gittercom Message Category Prediction." In 2024 OITS International Conference on Information Technology (OCIT). IEEE, 2024. https://doi.org/10.1109/ocit65031.2024.00041.

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Cui, Jianqun, Mengnan Gao, Yanan Chang, Huiran Yan, and Zhiyuan Ma. "DTN Routing Algorithm in Temporary Shelter based on Mobility Social Attributes and Message Destination Prediction." In 2024 IEEE International Conference on High Performance Computing and Communications (HPCC). IEEE, 2024. https://doi.org/10.1109/hpcc64274.2024.00123.

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Zhang, Xiaoping, Hui Feng, and Li Wang. "Cooperative Awareness Message Generation Interval Prediction Model Based on Bayesian Optimized Long Short-Term Memory Neural Network." In 2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2024. http://dx.doi.org/10.1109/ddcls61622.2024.10606549.

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Nawani, Tisha, Pratiksha Gangane, and Roshani Raut. "Unlocking insights: Exploring Whatsapp chats and Predicting spam messages." In 2024 International Conference on Computational Intelligence for Green and Sustainable Technologies (ICCIGST). IEEE, 2024. http://dx.doi.org/10.1109/iccigst60741.2024.10717538.

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Zhou, Mingyang, Yanjie Lin, Gang Liu, Zuwen Li, Hao Liao, and Rui Mao. "Modeling Personalized Retweeting Behaviors for Multi-Stage Cascade Popularity Prediction." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/287.

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Predicting the size of message cascades is critical in various applications, such as online advertising and early detection of rumors. However, most existing deep learning approaches rely on cascade observation, which hinders accurate cascade prediction before message posting. Besides, these approaches overlook personalized retweeting behaviors that reflect users' inclination to retweeting specific types of information. In this study, we propose a universal cascade prediction framework, namely Cascade prediction regarding Multiple Stage (CasMS), that effectively predicts cascade popularity acr
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Gazizullina, Alisa, and Manuel Mazzara. "Prediction of Twitter Message Deletion." In 2019 12th International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2019. http://dx.doi.org/10.1109/dese.2019.00031.

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Kinsey, Sarah, Jack Wolf, Nalini Saligram, et al. "Building a Personalized Messaging System for Health Intervention in Underprivileged Regions Using Reinforcement Learning." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/668.

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This work builds an effective AI-based message generation system for diabetes prevention in rural areas, where the diabetes rate has been increasing at an alarming rate. The messages contain information about diabetes causes and complications and the impact of nutrition and fitness on preventing diabetes. We propose to apply reinforcement learning (RL) to optimize our message selection policy over time, tailoring our messages to align with each individual participant's needs and preferences. We conduct an extensive field study in a large country in Asia which involves more than 1000 participan
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Shi, Yunsheng, Zhengjie Huang, Shikun Feng, Hui Zhong, Wenjing Wang, and Yu Sun. "Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/214.

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Graph neural network (GNN) and label propagation algorithm (LPA) are both message passing algorithms, which have achieved superior performance in semi-supervised classification. GNN performs feature propagation by a neural network to make predictions, while LPA uses label propagation across graph adjacency matrix to get results. However, there is still no effective way to directly combine these two kinds of algorithms. To address this issue, we propose a novel Unified Message Passaging Model (UniMP) that can incorporate feature and label propagation at both training and inference time. First,
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"Emoji Identification and Prediction in Hebrew Political Corpus." In InSITE 2019: Informing Science + IT Education Conferences: Jerusalem. Informing Science Institute, 2019. http://dx.doi.org/10.28945/4346.

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[This Proceedings paper was revised and published in the 2019 issue of the journal Issues in Informing Science and Information Technology, Volume 16] Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identifica
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Reports on the topic "Message prediction"

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Mylne, Ken. Communicating Probability Forecasts – will people understand? Met Office, 2024. https://doi.org/10.62998/bwjw5735.

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Executive Summary “People don’t understand probabilities” – or do they? Weather forecasting science has long been developing ensemble forecasts as a way to improve forecast capability and provide better information to support users’ decisions. The science is well proven and, indeed, the Met Office will soon move to an ensemble-only NWP (Numerical Weather Prediction) system. Ensemble forecasts can be used in a number of ways, but fundamentally they provide a probabilistic picture of the weather forecast including a most likely outcome and information on the confidence, uncertainty or risks asso
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Sánchez, Gabriel, Patricio Valenzuela, and Eduardo A. Cavallo. Gone with the Wind: Demographic Transitions and Domestic Saving. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0011730.

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This study explores the relationship between demographic factors and saving rates using a panel dataset covering 110 countries between 1963 and 2012. In line with predictions from theory, this paper finds that lower dependency rates and greater longevity increase domestic saving rates. However, these effects are statistically robust only in Asia. In particular, Latin America, which is a region that has undergone a remarkably similar demographic transition, did not experience the same boost in saving rates as Asia. The paper highlights that the potential dividends arising from a favorable demog
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Newmark, Gregory L. Measurement and Prediction of Transit System Performance Using Probe Data Generated through DSRC and non-DSRC Technologies. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2008.

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This research explores the application of two different probe data standards to transit performance measurement. The first section chronicles the proposed and implemented transit uses of dedicated short-range communication (DSRC) technologies during the two decades between the standard’s emergence and its announced sunset. The research finds that, despite proposed applications across safety, operation, and information domains, DSRC never became embedded in transit operations. By contrast, the general transit feed specification (GTFS) standard with its real-time (RT) extension has been widely e
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Hicks, Jacqueline. Health Workforce Interventions in Low-and-Middle-Income-Countries (LMICs). Institute of Development Studies, 2022. http://dx.doi.org/10.19088/k4d.2023.003.

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The clearest overall message from across the literature is that designing human resources for health (HRH) initiatives should begin by understanding the needs of a health system or population rather than choosing a specific strategy. In other words, there are no strategies that are universally effective, only strategies that are more or less appropriate to their context. One group of experienced researchers note the “difficulty in predicting how effective a strategy will be in a given context” (Rowe et al, 2018b). Another states that “in 2006, the World Health Report observed that a ‘solution
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Newmark, Gregory L. Assessing GTFS Accuracy. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2017.

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The promised benefits of the General Transit Feed Specification (GTFS) Schedule and Realtime standards are dependent on the underlying quality of the data. Despite this fundamental reliance, there has been relatively little research on techniques and strategies to assess GTFS accuracy. The need for such assessment is growing as federal and state governments increasingly require transit agencies to make these data available to the public. This research fills this gap by presenting a suite of methods and metrics to assess the temporal accuracy of GTFS Realtime and the spatial accuracy of GTFS Sc
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Smit, Amelia, Kate Dunlop, Nehal Singh, Diona Damian, Kylie Vuong, and Anne Cust. Primary prevention of skin cancer in primary care settings. The Sax Institute, 2022. http://dx.doi.org/10.57022/qpsm1481.

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Overview Skin cancer prevention is a component of the new Cancer Plan 2022–27, which guides the work of the Cancer Institute NSW. To lessen the impact of skin cancer on the community, the Cancer Institute NSW works closely with the NSW Skin Cancer Prevention Advisory Committee, comprising governmental and non-governmental organisation representatives, to develop and implement the NSW Skin Cancer Prevention Strategy. Primary Health Networks and primary care providers are seen as important stakeholders in this work. To guide improvements in skin cancer prevention and inform the development of th
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