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Relevant bibliographies by topics / User Intent Prediction

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Academic literature on the topic 'User Intent Prediction'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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Journal articles on the topic "User Intent Prediction"

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Santos, Eugene, Hien Nguyen, Qunhua Zhao, and Hua Wang. "User Modelling for Intent Prediction in Information Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 47, no. 8 (2003): 1034–38. http://dx.doi.org/10.1177/154193120304700818.

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Anirudh, Reddy Pathe. "Multi-Modal Feature Analysis for User Intent Prediction: A Framework for Enhanced Look-to-Book Ratio in Digital Platforms." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 5, no. 1 (2019): 1–10. https://doi.org/10.5281/zenodo.14282008.

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This research introduces an innovative framework for predicting user intent through multi-modal feature analysis, specifically designed to enhance look-to-book ratios in digital platforms. We present a comprehensive approach that leverages advanced machine learning techniques to process and analyze visual, textual, and behavioral data streams simultaneously. The framework incorporates novel feature fusion mechanisms and adaptive learning strategies to improve prediction accuracy while maintaining computational efficiency. Our theoretical analysis demonstrates the framework's potential for sign

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Para, Raghu K. "Intent Prediction in AR Shopping Experiences Using Multimodal Interactions of Voice, Gesture, and Eye Tracking: A Machine Learning Perspective." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 7, no. 01 (2024): 52–62. https://doi.org/10.60087/jaigs.v7i01.295.

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Augmented Reality (AR) is revolutionizing the shopping experience by allowing consumers to interact with virtual products in real-time. Intent prediction – the mechanism of predicting a consumer’s intention based on their behavioral patterns and actions – is crucial for enhancing the personalization of AR shopping environments. This paper explores how multimodal interactions, including voice commands, gesture recognition, and eye tracking, can be integrated into AR shopping experiences to predict user intent more effectively. We review current advancements in multimodal interaction systems, di

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Xiong, Wei, Michael Recce, and Brook Wu. "Intent-Based User Segmentation with Query Enhancement." International Journal of Information Retrieval Research 3, no. 4 (2013): 1–17. http://dx.doi.org/10.4018/ijirr.2013100101.

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With the rapid advancement of the internet, accurate prediction of user's online intent underlying their search queries has received increasing attention from online advertising community. This paper aims to address the major challenges with user queries in the context of behavioral targeting advertising by proposing a query enhancement mechanism that augments user's queries by leveraging a user query log. The empirical evaluation demonstrates that the authors' methodology for query enhancement achieves greater improvement than the baseline models in both intent-based user classification and u

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Isomoto, Toshiya, Shota Yamanaka, and Buntarou Shizuki. "Dwell Selection with ML-based Intent Prediction Using Only Gaze Data." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, no. 3 (2022): 1–21. http://dx.doi.org/10.1145/3550301.

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We developed a dwell selection system with ML-based prediction of a user's intent to select. Because a user perceives visual information through the eyes, precise prediction of a user's intent will be essential to the establishment of gaze-based interaction. Our system first detects a dwell to roughly screen the user's intent to select and then predicts the intent by using an ML-based prediction model. We created the intent prediction model from the results of an experiment with five different gaze-only tasks representing everyday situations. The intent prediction model resulted in an overall

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Xiao, Jingyu, Qingsong Zou, Qing Li, et al. "I Know Your Intent." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, no. 3 (2023): 1–28. http://dx.doi.org/10.1145/3610906.

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With the booming of smart home market, intelligent Internet of Things (IoT) devices have been increasingly involved in home life. To improve the user experience of smart homes, some prior works have explored how to use machine learning for predicting interactions between users and devices. However, the existing solutions have inferior User Device Interaction (UDI) prediction accuracy, as they ignore three key factors: routine, intent and multi-level periodicity of human behaviors. In this paper, we present SmartUDI, a novel accurate UDI prediction approach for smart homes. First, we propose a

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Cubuktepe, Murat, and Ufuk Topcu. "Intent Prediction in Shared Control with Delayed Feedback." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (2017): 733–34. http://dx.doi.org/10.1177/1541931213601668.

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In shared control, a robot and a human works together to accomplish a task in order to increase the efficiency of tele-operation. To assist the user in shared control, the robot has to predict the intent of the user accurately and quickly, but this may not be possible when the user can not adapt to the delay as the prediction of the robot depends of the inputs of the user. In this work, we propose an algorithm for intent prediction in shared control while providing performance guarantees when the user has a feedback delay. We assess the feasibility of our algorithm on a case study.

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Nematov, Ikhtiyor, Dimitris Sacharidis, Katja Hose, and Tomer Sagi. "AIDE: Antithetical, Intent-based, and Diverse Example-Based Explanations." Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7 (October 16, 2024): 1051–62. http://dx.doi.org/10.1609/aies.v7i1.31702.

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For many use-cases, it is often important to explain the prediction of a black-box model by identifying the most influential training data samples. Existing approaches lack customization for user intent and often provide a homogeneous set of explanation samples, failing to reveal the model's reasoning from different angles. In this paper, we propose AIDE, an approach for providing antithetical (i.e., contrastive), intent-based, diverse explanations for opaque and complex models. AIDE distinguishes three types of explainability intents: interpreting a correct, investigating a wrong, and clarify

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Li, Hourun, Yifan Wang, Zhiping Xiao, et al. "DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 12049–57. https://doi.org/10.1609/aaai.v39i11.33312.

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Recommender systems are widely used in various real-world applications, but they often encounter the persistent challenge of the user cold-start problem. Cross-domain recommendation (CDR), which leverages user interactions from one domain to improve prediction performance in another, has emerged as a promising solution. However, users with similar preferences in the source domain may exhibit different interests in the target domain. Therefore, directly transferring embeddings may introduce irrelevant source-domain collaborative information. In this paper, we propose a novel graph-based disenta

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Taplin, Tyler, Alexander E. Lyall, and Ashwin P. Dani. "Multiple User Intent Prediction Using Interacting Multiple Model Joint Probabilistic Data Association Filter." IFAC-PapersOnLine 56, no. 2 (2023): 6946–51. http://dx.doi.org/10.1016/j.ifacol.2023.10.515.

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Dissertations / Theses on the topic "User Intent Prediction"

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McNamara, Nathan Patrick. "Using Decision Trees to Predict Intent to Use Passive Occupational Exoskeletons in Manufacturing Tasks." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605720844135027.

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Roberts, David J. "A predictive real time architecture for multi-user, distributed, virtual reality." Thesis, University of Reading, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318140.

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Tang, Tang. "Active within Structures: An Empirical Integration of Individual, Structural and Technology Adoption Determinants in Predicting Internet Use." Ohio : Ohio University, 2008. http://www.ohiolink.edu/etd/view.cgi?ohiou1218041064.

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Mohammadi, Samin. "Analysis of user popularity pattern and engagement prediction in online social networks." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2018. http://www.theses.fr/2018TELE0019.

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De nos jours, les médias sociaux ont largement affecté tous les aspects de la vie humaine. Le changement le plus significatif dans le comportement des gens après l'émergence des réseaux sociaux en ligne (OSNs) est leur méthode de communication et sa portée. Avoir plus de connexions sur les OSNs apporte plus d'attention et de visibilité aux gens, où cela s'appelle la popularité sur les médias sociaux. Selon le type de réseau social, la popularité se mesure par le nombre d'adeptes, d'amis, de retweets, de goûts et toutes les autres mesures qui servaient à calculer l'engagement. L'étude du compor

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Mohammadi, Samin. "Analysis of user popularity pattern and engagement prediction in online social networks." Thesis, Evry, Institut national des télécommunications, 2018. http://www.theses.fr/2018TELE0019/document.

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De nos jours, les médias sociaux ont largement affecté tous les aspects de la vie humaine. Le changement le plus significatif dans le comportement des gens après l'émergence des réseaux sociaux en ligne (OSNs) est leur méthode de communication et sa portée. Avoir plus de connexions sur les OSNs apporte plus d'attention et de visibilité aux gens, où cela s'appelle la popularité sur les médias sociaux. Selon le type de réseau social, la popularité se mesure par le nombre d'adeptes, d'amis, de retweets, de goûts et toutes les autres mesures qui servaient à calculer l'engagement. L'étude du compor

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Bizid, Imen. "Prominent microblog users prediction during crisis events : using phase-aware and temporal modeling of users behavior." Thesis, La Rochelle, 2016. http://www.theses.fr/2016LAROS026/document.

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Durant les situations de crise, telles que les catastrophes, le besoin de recherche d’informations (RI) pertinentes partagées dans les microblogs en temps réel est inévitable. Cependant, le grand volume et la variété des flux d’informations partagées en temps réel dans de telles situations compliquent cette tâche. Contrairement aux approches existantes de RI basées sur l’analyse du contenu, nous proposons de nous attaquer à ce problème en nous basant sur les approches centrées utilisateurs tout en levant un certain nombre de verrous méthodologiques et technologiques inhérents : 1) à la collect

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Lieti, Valerio. "Development of an Industrial IoT End-to-End Use Case." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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This project is born merging my personal interest in IoT and AI fields and the collaboration with WiLab, Bi-rex and EBWorld. By joining different skills, the final result is the realization of an end-to-end Industrial IoT application. This IIoT use-case focuses on monitoring accelerations that characterize a turntable, on which mechanical parts are processed. The purpose of the monitoring is to implement predictive maintenance to report potential malfunctions. The turntable in question belongs to DMG Mori, a five-axis turning and milling machine for subtractive manufacturing, machine located a

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Raad, Elie. "Découverte des relations dans les réseaux sociaux." Phd thesis, Université de Bourgogne, 2011. http://tel.archives-ouvertes.fr/tel-00702269.

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Les réseaux sociaux occupent une place de plus en plus importante dans notre vie quotidienne et représentent une part considérable des activités sur le web. Ce succès s'explique par la diversité des services/fonctionnalités de chaque site (partage des données souvent multimédias, tagging, blogging, suggestion de contacts, etc.) incitant les utilisateurs à s'inscrire sur différents sites et ainsi à créer plusieurs réseaux sociaux pour diverses raisons (professionnelle, privée, etc.). Cependant, les outils et les sites existants proposent des fonctionnalités limitées pour identifier et organiser

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Sharp, Melanie. "Validation of self-reports for use in contact research." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:3ee1df93-1a91-4645-b298-d1d2a80853ff.

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The aim of this thesis was to investigate whether self-report measures of contact are valid for use in research testing the ‘contact hypothesis’. The vast majority of contact research has relied on the assumed validity of self-report methods of data collection (Pettigrew & Tropp, 2006), even though the potential weaknesses of self-report methodology generally have been well documented. This reliance is necessary, as self-reports remain the only practical method so far developed of measuring certain of the facilitating conditions developed by Allport (1954/1979), and particularly of direct and

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Lee, Joonghwa. "Predicting the use of online video advertising using the theory of planned behavior /." Diss., 2008.

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Books on the topic "User Intent Prediction"

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Proryv v budushchee: Sot︠s︡iologii︠a︡ internet-revoli︠u︡t︠s︡ii. O.G.I., 2007.

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Cross, Mary. Bloggerati, Twitterati. ABC-CLIO, LLC, 2011. http://dx.doi.org/10.5040/9798400620065.

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As timely as the latest tweet, this book tracks the digital revolution as a paradigm shift that is transforming popular culture in as yet unforeseen ways. Bloggerati, Twitterati: How Blogs and Twitter Are Transforming Popular Culture explores the ongoing digital revolution and examines the way it is changing—and will change—the way people live and communicate. Starting from the proposition that the Internet is now the center of popular culture, the book offers descriptions of blogs and Twitter and the online behavior they foster. It looks at the demographics of users and the impact of the Inte

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Castel, Alan D., Catherine D. Middlebrooks, and Shannon McGillivray. Monitoring Memory in Old Age. Edited by John Dunlosky and Sarah (Uma) K. Tauber. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199336746.013.3.

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Although a variety of memory changes accompany old age, an important question is the degree to which older adults are aware of these changes, and how older adults may or may not accurately monitor their own memory. Monitoring refers to the ability to assess how well one will remember certain information at a later time. In some cases, older adults may be overconfident about memory performance, whereas, in other situations, older adults may be highly aware of their memory abilities and demonstrate appropriate predictions and insight. This chapter will provide an overview of current research reg

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Susskind, Richard. Online Courts and the Future of Justice. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838364.001.0001.

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In Online Courts and the Future of Justice, Richard Susskind, the world’s most cited author on the future of legal services, shows how litigation will be transformed by technology and proposes a solution to the global access-to-justice problem. In most advanced legal systems, the resolution of civil disputes takes too long, costs too much, and the process is not just antiquated; it is unintelligible to ordinary mortals. The courts of some jurisdictions are labouring under staggering backlogs - 100 million cases in Brazil, 30 million in India. More people in the world now have internet access t

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Ransom, Barbara, and Sonya Wainwright. Recent Advances and Issues in the Geological Sciences. Greenwood Publishing Group, Inc., 2001. http://dx.doi.org/10.5040/9798216005889.

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While earthquakes and volcanic eruptions are shaking up the world, there are more exciting happenings in the diverse field of geological science. This fascinating look at the discipline of geology during the past 3 to 4 years casts an eye toward future directions and showcases new ideas and ways of thinking. The broad discipline of geology is as diverse and complex as the planet itself. The most recent advances in the field such as the debate about life on Mars and the melting of the polar ice caps are included. Special attention is given to the changing role of the practicing geologist from t

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Day, David. Antarctica. Oxford University Press, 2019. http://dx.doi.org/10.1093/wentk/9780190641320.001.0001.

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Part of the What Everyone Needs to Know® series, David Day's book on Antarctica examines the most forbidding and formidably inaccessible continent on Earth. Antarctica was first discovered by European explorers in 1820, and for over a century following this, countries competed for the frozen land's vast marine resources--namely, the skins and oil of seals and whales. Soon the entire territory played host to competing claims by rival nations. The Antarctic Treaty of 1959 was meant to end this contention, but countries have found other means of extending control over the land, with scientific ba

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Gorman, Sara E., and Jack M. Gorman. Denying to the Grave. Oxford University Press, 2016. http://dx.doi.org/10.1093/oso/9780199396603.001.0001.

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Why do some parents refuse to vaccinate their children? Why do some people keep guns at home, despite scientific evidence of risk to their family members? And why do people use antibiotics for illnesses they cannot possibly alleviate? When it comes to health, many people insist that science is wrong, that the evidence is incomplete, and that unidentified hazards lurk everywhere. In Denying to the Grave, Gorman and Gorman, a father-daughter team, explore the psychology of health science denial. Using several examples of such denial as test cases, they propose six key principles that may lead in

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Hoveyda, Fereydoun. The Hidden Meaning of Mass Communications. Praeger, 2000. http://dx.doi.org/10.5040/9798400663246.

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In 1917, the French poet Guillaume Apollinaire predicted the death of books in one or two centuries and their replacement by film and sound. In the early sixties, Marshall McLuhan proclaimed the end of the Gutenberg Galaxy. Neither of these predictions has yet happened. Nonetheless, the development of computer science and the spread of the Internet have already changed the landscape of the media and affected the fields of book publishing, journalism, cinema, and television. In his new book, Hoveyda, who was involved with cinema and literature for many years, scrutinizes the relationship betwee

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Book chapters on the topic "User Intent Prediction"

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Kalatzis, Nikos, Ioanna Roussaki, Nicolas Liampotis, Pavlos Kosmides, Ioannis Papaioannou, and Miltiades Anagnostou. "Context and Community Awareness in Support of User Intent Prediction." In Context in Computing. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1887-4_23.

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Luo, Yuyu, Zhenjie Huang, Leung-Pun Wong, Choujun Zhan, Fu Lee Wang, and Tianyong Hao. "An Early Prediction and Label Smoothing Alignment Strategy for User Intent Classification of Medical Queries." In Neural Computing for Advanced Applications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-6142-7_9.

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Simner, Ben, Shaked Flur, Christopher Pulte, et al. "ARMv8-A System Semantics: Instruction Fetch in Relaxed Architectures." In Programming Languages and Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44914-8_23.

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AbstractComputing relies on architecture specifications to decouple hardware and software development. Historically these have been prose documents, with all the problems that entails, but research over the last ten years has developed rigorous and executable-as-test-oracle specifications of mainstream architecture instruction sets and “user-mode” concurrency, clarifying architectures and bringing them into the scope of programming-language semantics and verification. However, the system semantics, of instruction-fetch and cache maintenance, exceptions and interrupts, and address translation, remains obscure, leaving us without a solid foundation for verification of security-critical systems software.In this paper we establish a robust model for one aspect of system semantics: instruction fetch and cache maintenance for ARMv8-A. Systems code relies on executing instructions that were written by data writes, e.g. in program loading, dynamic linking, JIT compilation, debugging, and OS configuration, but hardware implementations are often highly optimised, e.g. with instruction caches, linefill buffers, out-of-order fetching, branch prediction, and instruction prefetching, which can affect programmer-observable behaviour. It is essential, both for programming and verification, to abstract from such microarchitectural details as much as possible, but no more. We explore the key architecture design questions with a series of examples, discussed in detail with senior Arm staff; capture the architectural intent in operational and axiomatic semantic models, extending previous work on “user-mode” concurrency; make these models executable as test oracles for small examples; and experimentally validate them against hardware behaviour (finding a bug in one hardware device). We thereby bring these subtle issues into the mathematical domain, clarifying the architecture and enabling future work on system software verification.

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Trabelsi, Chiraz, Bilel Moulahi, and Sadok Ben Yahia. "Folksonomy Query Suggestion via Users’ Search Intent Prediction." In Flexible Query Answering Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24764-4_34.

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Schmitt, R. H., R. Kiesel, D. Buschmann, et al. "Improving Shop Floor-Near Production Management Through Data-Driven Insights." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_16-1.

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AbstractIn short-term production management of the Internet of Production (IoP) the vision of a Production Control Center is pursued, in which interlinked decision-support applications contribute to increasing decision-making quality and speed. The applications developed focus in particular on use cases near the shop floor with an emphasis on the key topics of production planning and control, production system configuration, and quality control loops.Within the Predictive Quality application, predictive models are used to derive insights from production data and subsequently improve the process- and product-related quality as well as enable automated Root Cause Analysis. The Parameter Prediction application uses invertible neural networks to predict process parameters that can be used to produce components with desired quality properties. The application Production Scheduling investigates the feasibility of applying reinforcement learning to common scheduling tasks in production and compares the performance of trained reinforcement learning agents to traditional methods. In the two applications Deviation Detection and Process Analyzer, the potentials of process mining in the context of production management are investigated. While the Deviation Detection application is designed to identify and mitigate performance and compliance deviations in production systems, the Process Analyzer concept enables the semi-automated detection of weaknesses in business and production processes utilizing event logs.With regard to the overall vision of the IoP, the developed applications contribute significantly to the intended interdisciplinary of production and information technology. For example, application-specific digital shadows are drafted based on the ongoing research work, and the applications are prototypically embedded in the IoP.

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Schmitt, Robert H., Raphael Kiesel, Daniel Buschmann, et al. "Improving Shop Floor-Near Production Management Through Data-Driven Insights." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-44497-5_16.

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AbstractIn short-term production management of the Internet of Production (IoP) the vision of a Production Control Center is pursued, in which interlinked decision-support applications contribute to increasing decision-making quality and speed. The applications developed focus in particular on use cases near the shop floor with an emphasis on the key topics of production planning and control, production system configuration, and quality control loops.Within the Predictive Quality application, predictive models are used to derive insights from production data and subsequently improve the process- and product-related quality as well as enable automated Root Cause Analysis. The Parameter Prediction application uses invertible neural networks to predict process parameters that can be used to produce components with desired quality properties. The application Production Scheduling investigates the feasibility of applying reinforcement learning to common scheduling tasks in production and compares the performance of trained reinforcement learning agents to traditional methods. In the two applications Deviation Detection and Process Analyzer, the potentials of process mining in the context of production management are investigated. While the Deviation Detection application is designed toidentify and mitigate performance and compliance deviations in production systems, the Process Analyzer concept enables the semi-automated detection of weaknesses in business and production processes utilizing event logs.With regard to the overall vision of the IoP, the developed applications contribute significantly to the intended interdisciplinary of production and information technology. For example, application-specific digital shadows are drafted based on the ongoing research work, and the applications are prototypically embedded in the IoP.

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Heghedus, Cristina, and Chunming Rong. "Artificial Intelligence Models Used for Prediction in the Energy Internet." In Energy Internet. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45453-1_11.

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Benabbou, Faouzia, Nawal Sael, and Imad Herchy. "Machine Learning for Used Cars Price Prediction: Moroccan Use Case." In Proceedings of the 5th International Conference on Big Data and Internet of Things. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07969-6_25.

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Pignocchino, Gianmarco, Alessandro Pezzoli, and Angelo Besana. "Satellite Data and Epidemic Cartography: A Study of the Relationship Between the Concentration of NO2 and the COVID-19 Epidemic." In Communications in Computer and Information Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94426-1_5.

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AbstractSatellite data are widely used to study the spatial component of epidemics: to monitor their evolution, to create epidemiological risk maps and predictive models. The improvement of data quality, not only in technical terms but also of scientific relevance and robustness, represents in this context one of the most important aspects for health information technology that can make further significant and useful progress in monitoring and managing epidemics. In this regard, this paper intends to address an issue that is not always adequately considered in the use of satellite data for the creation of maps and spatial models of epidemics, namely the preliminary verification of the level of spatial correlation between remote sensing environmental variables and epidemics. Specifically, we intend to evaluate the contribution of exposure to the pollutant nitrogen dioxide (NO2) on the spatial spread of the virus and the severity of the current COVID infection.

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Rathore, Nemi Chandra, Somanath Tripathy, and Joydeep Chandra. "Predicting User Visibility in Online Social Networks Using Local Connectivity Properties." In Distributed Computing and Internet Technology. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14977-6_46.

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Conference papers on the topic "User Intent Prediction"

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Sharma, P., A. Meshaikhis, C. Ennaceur, et al. "CUI Monitoring for Cold Duty Insulation, Evaluation and Use Cases." In MECC 2023. AMPP, 2023. https://doi.org/10.5006/mecc2023-20256.

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Abstract Predictive Corrosion Management have a lot of attractive use cases including Corrosion Under Insulation (CUI) enabled by monitoring and Artificial Intelligence (AI). This paper describes the deployment and evaluation of remote monitoring solution with application in corrosion under insulation management especially for cold duty insulation with intermittent service. A remote Monitoring system using Electro-Magnetic Guided Radar (EMGR) is described in this paper that uses advanced analytics for predictions. This technology involves use of sensors embedded in the insulation and a data lo

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Kapusta, S. D., B. F. M. Pots, and R. A. Connell. "Corrosion Management of Wet Gas Pipelines." In CORROSION 1999. NACE International, 1999. https://doi.org/10.5006/c1999-99045.

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Abstract This paper describes an approach to the design of carbon steel pipelines operating in corrosive service. The intent of this approach is to take full advantage of the reduced costs of carbon steel, while minimising the risk of failures. This approach is based on: (1) assessing the technical and economic feasibility of carbon steel; (2) designing the pipeline for corrosive service, which mainly means designing the corrosion control system; and (3) implementing a corrosion management programme to ensure that corrosion control is properly applied. Industry wide experience shows that carbo

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Sun, Fengxiao, Qingcui Hu, Meiling Yao, and Chi Xu. "Urban meteorological sensing and prediction system based on augmented reality and MQTT: An exploration of user-side immersive display technology." In 4th International Conference on Internet of Things and Smart City, edited by Xinwei Yao and Francisco Falcone. SPIE, 2024. http://dx.doi.org/10.1117/12.3034852.

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Zhang, X. G., S. Alhassan, and F. E. Goodwin. "Predicting Life of Galvanised Steel on Internet." In CORROSION 2004. NACE International, 2004. https://doi.org/10.5006/c2004-04067.

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Abstract The ability to predict corrosion life has always been important for effective application of galvanised steel products. In this paper, an Internet based software developed to predict the life of zinc coatings is introduced. The scientific methodology and development process for the prediction models will be described. Considerations for the design of the software with regard to scientific clarity, requirements of end users, and scope of application will be discussed. An evaluation of the accuracy of prediction using recently published data will be presented.

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Lee, Kenton C. T., Anca D. Dragan, and Siddhartha S. Srinivasa. "Legible user input for intent prediction." In 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 2013. http://dx.doi.org/10.1109/hri.2013.6483558.

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Qu, Chen, Liu Yang, W. Bruce Croft, Yongfeng Zhang, Johanne R. Trippas, and Minghui Qiu. "User Intent Prediction in Information-seeking Conversations." In CHIIR '19: Conference on Human Information Interaction and Retrieval. ACM, 2019. http://dx.doi.org/10.1145/3295750.3298924.

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Wang, Peng, Jiang Xu, Chunyi Liu, Hao Feng, Zang Li, and Jieping Ye. "Masked-field Pre-training for User Intent Prediction." In CIKM '20: The 29th ACM International Conference on Information and Knowledge Management. ACM, 2020. http://dx.doi.org/10.1145/3340531.3412726.

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Chen, Cen, Chilin Fu, Xu Hu, et al. "Reinforcement Learning for User Intent Prediction in Customer Service Bots." In SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2019. http://dx.doi.org/10.1145/3331184.3331370.

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Pan, Mao, Tao Yu, Kun Zhou, et al. "IUI: Intent-Enhanced User Interest Modeling for Click-Through Rate Prediction." In CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management. ACM, 2023. http://dx.doi.org/10.1145/3583780.3614939.

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He, Yacheng, Qianghuai Jia, Lin Yuan, Ruopeng Li, Yixin Ou, and Ningyu Zhang. "A Concept Knowledge Graph for User Next Intent Prediction at Alipay." In WWW '23: The ACM Web Conference 2023. ACM, 2023. http://dx.doi.org/10.1145/3543873.3587308.

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Reports on the topic "User Intent Prediction"

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Shmulevich, Itzhak, Shrini Upadhyaya, Dror Rubinstein, Zvika Asaf, and Jeffrey P. Mitchell. Developing Simulation Tool for the Prediction of Cohesive Behavior Agricultural Materials Using Discrete Element Modeling. United States Department of Agriculture, 2011. http://dx.doi.org/10.32747/2011.7697108.bard.

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The underlying similarity between soils, grains, fertilizers, concentrated animal feed, pellets, and mixtures is that they are all granular materials used in agriculture. Modeling such materials is a complex process due to the spatial variability of such media, the origin of the material (natural or biological), the nonlinearity of these materials, the contact phenomenon and flow that occur at the interface zone and between these granular materials, as well as the dynamic effect of the interaction process. The lack of a tool for studying such materials has limited the understanding of the phen

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Sadegh, Mojtaba, Seyd Seydi, John Abatzoglou, Amir AghaKouchak, Mir Matin, and Kaveh Madani. January 2025 Los Angeles Wildfires: Once-in-a-Generation Events Now Happen Frequently. United Nations University Institute for Water, Environment and Health (UNU INWEH), 2025. https://doi.org/10.53328/inr25mos003.

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1. On January 7, 2025, Palisades and Eaton fires started and burned through urban areas of Los Angeles County, California. They collectively destroyed nearly 16,250 structures, and directly exposed ~41,000 people, ranking them 2nd and 3rd most destructive wildfires in California’s history1. 2. Started during drought conditions coincident with the Santa Ana winds with wind gusts exceeding 100 miles per hour, the fires rapidly spread into densely populated urban areas, resulting in 29 fatalities and widespread population displacement. 3. The January 2025 Los Angeles wildfires underscore the incr

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MR MSK Cartilage for Joint Disease, Consensus Profile. Chair Thomas Link and Xiaojuan Li. Radiological Society of North America (RSNA) / Quantitative Imaging Biomarkers Alliance (QIBA), 2021. http://dx.doi.org/10.1148/qiba/20210925.

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The goal of a QIBA Profile is to help achieve a useful level of performance for a given biomarker. The Claim (Section 2) describes the biomarker performance. The Activities (Section 3) contribute to generating the biomarker. Requirements are placed on the Actors that participate in those activities as necessary to achieve the Claim. Assessment Procedures (Section 4) for evaluating specific requirements are defined as needed. This QIBA Profile (MR-based cartilage compositional biomarkers (T1ρ, T2) ) addresses the application of T1ρ and T2 for the quantification of cartilage composition, which c

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99mTc SPECT-CT, Consensus QIBA Profile. Chair Yuni Dewaraja and Robert Miyaoka. Radiological Society of North America (RSNA)/Quantitative Imaging Biomarkers Alliance (QIBA), 2019. https://doi.org/10.1148/qiba/20191021.

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The quantification of 99mTc labeled biomarkers can add unique value in many different settings, ranging from clinical trials of investigation new drugs to the treatment of individual patients with marketed therapeutics. For example, goals of precision medicine include using companion radiopharmaceutical diagnostics as just-in-time, predictive biomarkers for selecting patients to receive targeted treatments, customizing doses of internally administered radiotherapeutics, and assessing responses to treatment. This Profile describes quantitative outcome measures that represent proxies of target c

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Elizur, Abigail, Amir Sagi, Gideon Hulata, Clive Jones, and Wayne Knibb. Improving Crustacean Aquaculture Production Efficiencies through Development of Monosex Populations Using Endocrine and Molecular Manipulations. United States Department of Agriculture, 2010. http://dx.doi.org/10.32747/2010.7613890.bard.

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Background Most of Australian prawn aquaculture production is based on P. monodon. However, the Australian industry is under intense competition from lower priced overseas imports. The availability of all-female monosex populations, by virtue of their large size and associated premium prize, will offer competitive advantage to the industry which desperately needs to counteract competitors within this market. As for the redclaw production in Israel, although it is at its infancy, the growers realized that the production of males is extremely advantageous and that such management strategy will c

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