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Decision making

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Full-Text Articles in Physical Sciences and Mathematics

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens May 2024

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …

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Ethical Decision-Making In Older Drivers During Critical Driving Situations: An Online Experiment, Amandeep Singh, Sarah Yahoodik, Yovela Murzello, Samuel Petkac, Yusuke Yamani, Siby Samuel Jan 2024

Ethical Decision-Making In Older Drivers During Critical Driving Situations: An Online Experiment, Amandeep Singh, Sarah Yahoodik, Yovela Murzello, Samuel Petkac, Yusuke Yamani, Siby Samuel

Psychology Faculty Publications

The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios. 204 participants from North America, grouped into two age groups (18–30 years and 65 years and above), were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem. Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment. Bayesian hierarchical models were used to analyze …

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Utility In Time Description In Priority Best-Worst Discrete Choice Models: An Empirical Evaluation Using Flynn's Data, Sasanka Adikari, Norou Diawara Jan 2024

Utility In Time Description In Priority Best-Worst Discrete Choice Models: An Empirical Evaluation Using Flynn's Data, Sasanka Adikari, Norou Diawara

Mathematics & Statistics Faculty Publications

Discrete choice models (DCMs) are applied in many fields and in the statistical modelling of consumer behavior. This paper focuses on a form of choice experiment, best-worst scaling in discrete choice experiments (DCEs), and the transition probability of a choice of a consumer over time. The analysis was conducted by using simulated data (choice pairs) based on data from Flynn's (2007) 'Quality of Life Experiment'. Most of the traditional approaches assume the choice alternatives are mutually exclusive over time, which is a questionable assumption. We introduced a new copula-based model (CO-CUB) for the transition probability, which can handle the dependent …

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A Systemic Mapping Study On Intrusion Response Systems, Adel Rezapour, Mohammad Ghasemigol, Daniel Takabi Jan 2024

A Systemic Mapping Study On Intrusion Response Systems, Adel Rezapour, Mohammad Ghasemigol, Daniel Takabi

School of Cybersecurity Faculty Publications

With the increasing frequency and sophistication of network attacks, network administrators are facing tremendous challenges in making fast and optimum decisions during critical situations. The ability to effectively respond to intrusions requires solving a multi-objective decision-making problem. While several research studies have been conducted to address this issue, the development of a reliable and automated Intrusion Response System (IRS) remains unattainable. This paper provides a Systematic Mapping Study (SMS) for IRS, aiming to investigate the existing studies, their limitations, and future directions in this field. A novel semi-automated research methodology is developed to identify and summarize related works. The innovative …

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Context-Driven Behavior: Improved Contextual Reasoning For Context-Aware Agents, Christian L. Wilson Dec 2023

Context-Driven Behavior: Improved Contextual Reasoning For Context-Aware Agents, Christian L. Wilson

Electronic Theses and Dissertations

Over the last three decades, a considerable amount of research has been dedicated to improving an artificial agent's ability to recognize and deal effectively with context. In this paper, I discuss a framework for a novel form of contextual reasoning. Unlike existing contextual reasoning frameworks, which allow an agent to apply its contextual knowledge after it is operating in an instance of a known context, the model I discuss allows an agent to reason about context proactively. With a proactive model, an agent forecasts the future contexts it will encounter, then takes steps to ensure its behaviors are appropriate for …

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When Is A Single "And"-Condition Enough?, Olga Kosheleva, Vladik Kreinovich Dec 2023

When Is A Single "And"-Condition Enough?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, there are several possible decisions. Any general recommendation means specifying, for each possible decision, conditions under which this decision is recommended. In some cases, a single "and"-condition is sufficient: e.g., a condition under which a patient is recommended to take aspirin is that "the patient has a fever and the patient does not have stomach trouble". In other cases, conditions are more complicated. A natural question is: when is a single "and"-condition enough? In this paper, we provide an answer to this question.

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Human-Centered Technologies For Inclusive Collection And Analysis Of Public-Generated Data, Mahmood Jasim Nov 2023

Human-Centered Technologies For Inclusive Collection And Analysis Of Public-Generated Data, Mahmood Jasim

Doctoral Dissertations

The meteoric rise in the popularity of public engagement platforms such as social media, customer review websites, and public input solicitation efforts strives for establishing an inclusive environment for the public to share their thoughts, ideas, opinions, and experiences. Many decisions made at a personal, local, or national scale are often fueled by data generated by the public. As such, inclusive collection, analysis, sensemaking, and utilization of pubic-generated data are crucial to support the exercise of successful decision-making processes. However, people often struggle to engage, participate, and share their opinions due to inaccessibility, the rigidity of traditional public engagement methods, …

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Visually Analyzing Company-Wide Software Service Dependencies: An Industrial Case Study, Sebastian Baltes, Brian Pfitzmann, Thomas Kowark, Christoph Treude, Fabian Beck Oct 2023

Visually Analyzing Company-Wide Software Service Dependencies: An Industrial Case Study, Sebastian Baltes, Brian Pfitzmann, Thomas Kowark, Christoph Treude, Fabian Beck

Research Collection School Of Computing and Information Systems

Managing dependencies between software services is a crucial task for any company operating cloud applications. Visualizations can help to understand and maintain these com-plex dependencies. In this paper, we present a force-directed service dependency visualization and filtering tool that has been developed and used within SAP. The tool's use cases include guiding service retirement as well as understanding service deployment landscapes and their relationship to the company's organizational structure. We report how we built and adapted the tool under strict time constraints to address the requirements of our users. We further share insights on how we enabled internal adoption. For …

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How To Make Decision Under Interval Uncertainty: Description Of All Reasonable Partial Orders On The Set Of All Intervals, Tiago M. Costa, Olga Kosheleva, Vladik Kreinovich Jul 2023

How To Make Decision Under Interval Uncertainty: Description Of All Reasonable Partial Orders On The Set Of All Intervals, Tiago M. Costa, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we need to make a decision while for each alternative, we only know the corresponding value of the objective function with interval uncertainty. To help a decision maker in this situation, we need to know the (in general, partial) order on the set of all intervals that corresponds to the preferences of the decision maker. For this purpose, in this paper, we provide a description of all such partial orders -- under some reasonable conditions. It turns out that each such order is characterized by two linear inequalities relating the endpoints of the corresponding intervals, and …

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Targeted Seasonal Climate Forecasts Offer More To Pastoralists, David H. Cobon, J. N. Park, K. L. Bell, I. W. Watson, W. Fletcher, M. Young Jun 2023

Targeted Seasonal Climate Forecasts Offer More To Pastoralists, David H. Cobon, J. N. Park, K. L. Bell, I. W. Watson, W. Fletcher, M. Young

IGC Proceedings (1997-2023)

The existing forecast systems such as the Southern Oscillation Index (SOI) phase system (Stone et al., 1996) and the Sea Surface Temperature (SST) phase system (Drosdowsky 2002) produce rolling three monthly forecasts with lead-times of either zero (SOI phase) or 1 month (SST phase). Both forecasts are reissued monthly. This approach leaves little time for pastoralists to consider the forecast and then make changes to management decisions. In addition the forecast period can often be of little interest because of the seasonal pattern of rainfall.

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Validation Of Faecal Nirs For Monitoring The Diet Of Confined And Grazing Goats, S. Y. Landau, T. A. Glasser, L. Dvash, Avi Perevolotsky Jun 2023

Validation Of Faecal Nirs For Monitoring The Diet Of Confined And Grazing Goats, S. Y. Landau, T. A. Glasser, L. Dvash, Avi Perevolotsky

IGC Proceedings (1997-2023)

Goats are used for brush control and ecological management of Mediterranean grazing lands. Farmers are willing to cooperate with communities but they need an easy method to evaluate the daily intake of nutrients. A calibration of the chemical attributes of goats' diets was set-up, based on faecal near infrared (NIR) spectra (Landau et al., 2004; Table 1). The accuracy of this methodology was estimated by using the standard error of cross-validation (SECV), which represents the variability in the difference between predicted and reference values when the equation is applied sequentially to subsets of data from the calibration data set. …

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A Survey On Online Matching And Ad Allocation, Ryan Lee May 2023

A Survey On Online Matching And Ad Allocation, Ryan Lee

Theses

One of the classical problems in graph theory is matching. Given an undirected graph, find a matching which is a set of edges without common vertices. In 1990s, Richard Karp, Umesh Vazirani, and Vijay Vazirani would be the first computer scientists to use matchings for online algorithms [8]. In our domain, an online algorithm operates in the online setting where a bipartite graph is given. On one side of the graph there is a set of advertisers and on the other side we have a set of impressions. During the online phase, multiple impressions will arrive and the objective of …

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Developing Young Science And Technology Parks: Recent Findings From Industrial Nations Using The Data-Driven Approach, Charles Mondal, Mousa Al-Kfairy, Robert B. Mellor Apr 2023

Developing Young Science And Technology Parks: Recent Findings From Industrial Nations Using The Data-Driven Approach, Charles Mondal, Mousa Al-Kfairy, Robert B. Mellor

All Works

Science and technology parks (STPs) are curated locations where new technology-based firms (NTBFs) and other SMEs and firms can conglomerate and promote a culture of innovation. Overall, the aim is to construct a sustainable high-value tech entrepreneurship ecosystem, and to this end we present here some recent and novel concepts derived from approaches using a data-driven statistical foundation. This paper considers studies on the organic growth of young start-up science and technology parks by authors who have used big data, econometric analyses, panel data and computer simulations. The results and concepts are derived from industrialized countries, notably Sweden and the …

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A Study Of The Impact Of Data Intelligence On Software Delivery Performance, Yongdong Dong Mar 2023

A Study Of The Impact Of Data Intelligence On Software Delivery Performance, Yongdong Dong

Dissertations and Theses Collection (Open Access)

With the rise of big data and artificial intelligence, data intelligence has gradually become the focus of academia and industry. Data intelligence has two obvious characteristics: big data drive and application scene drive. More and more enterprises extract valuable patterns contained in data with prediction and decision analysis methods and technologies such as large-scale data mining, machine learning and deep learning and use them to improve the management and decision in complex practice, so as to promote changes of new business modes, organizational structures and even business strategies, and improve the operational efficiency of organizations. However, there are few studies …

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Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll Feb 2023

Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Uncertainties are difficult if not impossible to avoid. Capturing data from the analog world almost always results in some form of uncertainty. The amount of uncertainty depends on the method of measurement and its accuracy. When visualizing data that has some associated uncertainty, it is essential to properly process and convey such uncertainty and especially the amount of uncertainty keeping in mind that additional processing steps can amplify the uncertainty. There are various sources of uncertainty, such as numerical limitations or limitations of the capture device. However, there are other sources of uncertainty. Some of these uncertainties stem from model …

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Unifying Threats Against Information Integrity In Participatory Crowd Sensing, Shameek Bhattacharjee, Sajal K. Das Jan 2023

Unifying Threats Against Information Integrity In Participatory Crowd Sensing, Shameek Bhattacharjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

This article proposes a unified threat landscape for participatory crowd sensing (P-CS) systems. Specifically, it focuses on attacks from organized malicious actors that may use the knowledge of P-CS platform's operations and exploit algorithmic weaknesses in AI-based methods of event trust, user reputation, decision-making, or recommendation models deployed to preserve information integrity in P-CS. We emphasize on intent driven malicious behaviors by advanced adversaries and how attacks are crafted to achieve those attack impacts. Three directions of the threat model are introduced, such as attack goals, types, and strategies. We expand on how various strategies are linked with different attack …

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Types Of Questions Teachers Ask To Engage Students In Making Sense Of A Student Contribution, Nishat B. Alam Jan 2023

Types Of Questions Teachers Ask To Engage Students In Making Sense Of A Student Contribution, Nishat B. Alam

Dissertations, Master's Theses and Master's Reports

In the student-centered classroom, a teacher’s interpretation and response to student mathematical contributions plays an important role to shape and direct students’ opportunities for sense-making. This research used a scenario-based survey questionnaire to examine what types of questions middle and high school mathematics teachers indicate they would ask to engage students in making sense of a high-leverage student mathematical contribution and their reasoning about why particular questions are or are not productive. From the results, it could be concluded that teachers asked more productive questions after seeing a set of possible questions. Their beliefs about the productivity of the questions …

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Predictive Taxonomy Analytics (Lasso): Predicting Outcome Types Of Cyber Breach, Jing Rong Goh, Shaun S. Wang, Yaniv Harel, Gabriel Toh Jan 2023

Predictive Taxonomy Analytics (Lasso): Predicting Outcome Types Of Cyber Breach, Jing Rong Goh, Shaun S. Wang, Yaniv Harel, Gabriel Toh

Research Collection School Of Economics

Cyber breaches are costly for the global economy and extensive efforts have gone into improving the cybersecurity infrastructure. There are numerous types of cyber breaches that vary greatly in terms of cause and impact, resulting in an extensive literature for individual cyber breach type. Our paper seeks to provide a general framework that can be easily applied to analyze different types of cyber breaches. Our framework is inspired by the taxonomy approach in the cybersecurity literature, where it was proposed that an effective set of taxonomy can provide a direction on supporting improved decision-making in cyber risk management and selecting …

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Towards Improving Calibration In Object Detection Under Domain Shift, Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz, Mohsen Ali Dec 2022

Towards Improving Calibration In Object Detection Under Domain Shift, Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz, Mohsen Ali

Computer Vision Faculty Publications

With deep neural network based solution more readily being incorporated in real-world applications, it has been pressing requirement that predictions by such models, especially in safety-critical environments, be highly accurate and well-calibrated. Although some techniques addressing DNN calibration have been proposed, they are only limited to visual classification applications and in-domain predictions. Unfortunately, very little to no attention is paid towards addressing calibration of DNN-based visual object detectors, that occupy similar space and importance in many decision making systems as their visual classification counterparts. In this work, we study the calibration of DNN-based object detection models, particularly under domain shift. …

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The Distinction Of Logical Decision According To The Model Of The Analysis Of Brain Signals (Eeg), Akeel Abdulkareem Al-Sakaa, Zaid H. Nasralla, Mohsin Hasan Hussein, Saif A. Abd, Hazim Alsaqaa, Kesra Nermend, Anna Borawska Aug 2022

The Distinction Of Logical Decision According To The Model Of The Analysis Of Brain Signals (Eeg), Akeel Abdulkareem Al-Sakaa, Zaid H. Nasralla, Mohsin Hasan Hussein, Saif A. Abd, Hazim Alsaqaa, Kesra Nermend, Anna Borawska

Karbala International Journal of Modern Science

Recently, brain signal patterns have been recruited by researchers in different life activities. Researchers have studied each life activity and how brain signal patterns appear. These patterns could then be generalised and used in different disciplines. In this paper, we study the brain state during decision making in a lottery experiment. An EEG device is used to capture brain signals during an experiment to extract the optimal state for logical decision making. After collecting data, extracting useful information and then processing it, the proposed method is able to identify rational decisions from irrational ones with a success rate of 67%.

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Essays In Multidimensional Mechanism Design., Kolagani Paramahamsa Dr. May 2022

Essays In Multidimensional Mechanism Design., Kolagani Paramahamsa Dr.

Doctoral Theses

This thesis analyzes three problems where a monopolistic seller is selling to an agent with multidimensional private information. While our understanding of such problems is comprehensive if the agent's private information is one-dimensional, problems with multidimensional private information are known to be ubiquitous but analytically notorious. The three chapters in this thesis make progress in understanding optimal mechanism design in such multidimensional screening problems. In the first problem, the seller is selling an object to an agent who exhibits behavioral preferences, in a departure from the standard rational models. Behavioral preferences arise because the agent is budget constrained and needs …

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Heterogeneous Attentions For Solving Pickup And Delivery Problem Via Deep Reinforcement Learning, Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang Mar 2022

Heterogeneous Attentions For Solving Pickup And Delivery Problem Via Deep Reinforcement Learning, Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang

Research Collection School Of Computing and Information Systems

Recently, there is an emerging trend to apply deep reinforcement learning to solve the vehicle routing problem (VRP), where a learnt policy governs the selection of next node for visiting. However, existing methods could not handle well the pairing and precedence relationships in the pickup and delivery problem (PDP), which is a representative variant of VRP. To address this challenging issue, we leverage a novel neural network integrated with a heterogeneous attention mechanism to empower the policy in deep reinforcement learning to automatically select the nodes. In particular, the heterogeneous attention mechanism specifically prescribes attentions for each role of the …

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Death-Related Anxiety Associated With Riskier Decision-Making Irrespective Of Framing: A Bayesian Model Comparison, Blaine Tomkins Mar 2022

Death-Related Anxiety Associated With Riskier Decision-Making Irrespective Of Framing: A Bayesian Model Comparison, Blaine Tomkins

Psychology Faculty Publications

A commonly reported finding is that anxious individuals are less likely to make risky decisions. However, no studies have examined whether this association extends to death-related anxiety. The present study examined how groups low, moderate, and high in death-related anxiety make decisions with varying levels of risk. Participants completed a series of hypothetical bets in which the probability of a win was systematically manipulated. High-anxiety individuals displayed the greatest risk-taking behavior, followed by the moderate-anxiety group, with the low-anxiety group being most risk-averse. Experiment 2 tested this association further by framing outcomes in terms of losses, rather than gains. A …

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Factors Influencing Adoption Of Rangeland Rehabilitation Technologies By Agro-Pastoralists In The Arabian Peninsula: Evidence From Analysis In Saudi Arabia And Qatar, Boubaker Dhehibi, Arash Nejatian, Abdul Aziz Niane, Azaiez Ouled Belgacem Feb 2022

Factors Influencing Adoption Of Rangeland Rehabilitation Technologies By Agro-Pastoralists In The Arabian Peninsula: Evidence From Analysis In Saudi Arabia And Qatar, Boubaker Dhehibi, Arash Nejatian, Abdul Aziz Niane, Azaiez Ouled Belgacem

IGC Proceedings (1997-2023)

Rangelands are the main land use in the Arabian Peninsula and cover about 50% of total area. They are under continuous heavy grazing pressure due to underlying social and economic causes as well as institutional effects. ICARDA in collaboration with the National Agricultural Research Systems (NARS) has developed and introduced different rehabilitation techniques including resting, planting native range species and water harvesting in different countries of the AP such as Kuwait, Qatar, Saudi Arabia (KSA) and Yemen. However, the adoption of these techniques by end users was not evaluated. In this context, a research has been conducted in Saudi Arabia …

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Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub Feb 2022

Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub

Computer Vision Faculty Publications

For personalized medicines, very crucial intrinsic information is present in high dimensional omics data which is difficult to capture due to the large number of molecular features and small number of available samples. Different types of omics data show various aspects of samples. Integration and analysis of multi-omics data give us a broad view of tumours, which can improve clinical decision making. Omics data, mainly DNA methylation and gene expression profiles are usually high dimensional data with a lot of molecular features. In recent years, variational autoencoders (VAE) [13] have been extensively used in embedding image and text data into …

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The Data Analytics And The Science Revolution, Leila Halawi, Amal Clarke, Kelly George Feb 2022

The Data Analytics And The Science Revolution, Leila Halawi, Amal Clarke, Kelly George

Publications

This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead. The book combines the conceptual perspective and a hands-on approach to predictive analytics using SAS VIYA, an analytic and data management platform. The authors use SAS VIYA to focus on analytics to solve problems, highlight how analytics is applied in the airline and business environment, and compare several different modeling techniques. They decipher complex algorithms to demonstrate how they …

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Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr. Jan 2022

Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr.

Doctoral Theses

Evolutionary Algorithms (EAs) for Many-Objective Optimization (MaOO) problems are challenging in nature due to the requirement of large population size, difficulty in maintaining the selection pressure towards global optima and inability of accurate visualization of high-dimensional Pareto-optimal Set (in decision space) and Pareto-Front (in objective space). The quality of the estimated set of Pareto-optimal solutions, resulting from the EAs for MaOO problems, is assessed in terms of proximity to the true surface (convergence) and uniformity and coverage of the estimated set over the true surface (diversity). With more number of objectives, the challenges become more profound. Thus, better strategies have …

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Functional Implications Of Dale's Law In Balanced Neuronal Network Dynamics And Decision Making, Victor J. Barranca, Asha Bhuiyan , '23, Max Sundgren , '22, Fangzhou Xing , '22 Jan 2022

Functional Implications Of Dale's Law In Balanced Neuronal Network Dynamics And Decision Making, Victor J. Barranca, Asha Bhuiyan , '23, Max Sundgren , '22, Fangzhou Xing , '22

Mathematics & Statistics Faculty Works

The notion that a neuron transmits the same set of neurotransmitters at all of its post-synaptic connections, typically known as Dale's law, is well supported throughout the majority of the brain and is assumed in almost all theoretical studies investigating the mechanisms for computation in neuronal networks. Dale's law has numerous functional implications in fundamental sensory processing and decision-making tasks, and it plays a key role in the current understanding of the structure-function relationship in the brain. However, since exceptions to Dale's law have been discovered for certain neurons and because other biological systems with complex network structure incorporate individual …

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Business Intelligence Trends: A Review Of Mobile Business Intelligence, Shanika Edirisinghe Jan 2022

Business Intelligence Trends: A Review Of Mobile Business Intelligence, Shanika Edirisinghe

Articles

The early stages of Decision Support Systems evolved with the technological improvements and availability of massive amounts of data. The concept of Business Intelligence became apparent along with this evolution which incorporates a range of fields and supports decision making in business organizations. Mobile business intelligence is a popular trend in the domain of business intelligence at present. Business organizations employ mobile business intelligence as an extension to the existing business intelligence systems. This study intends to present a review of mobile business intelligence while addressing its benefits, challenges, and limitations. Moreover, this study provides details of several use cases …

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Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng Jan 2022

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

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