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Keyword: NLPOptimization of Investment in Decision – Making in Engineering Economy
Investment decision-making plays a pivotal role in shaping both individual and institutional economic outcomes. Given the increasing complexity and uncertainty in global markets, optimizing investment decisions has become essential for maximizing returns while managing risks. This work explores modern optimization approaches in investment decision-making, focusing on mathematical modeling techniques such as linear programming (LP), mixed-integer…
Read MoreA Review of Natural Language Processing Techniques in Under-Resourced Languages
Natural language processing (NLP) techniques have transformed a number of tasks in the modern age of information explosion where millions of gigabytes of data are generated every day. Despite achieving state-of-the-art performance in high-resource languages, current techniques struggle with processing under-resourced languages which are characterized by data scarcity, linguistic diversity, computational limitations, ambiguity of language…
Read MoreGenerative Artificial Intelligence and Prompt Engineering: A Comprehensive Guide to Models, Methods, and Best Practices
This article enhances discussions on Generative Artificial Intelligence (GenAI) and prompt engineering by exploring critical pitfalls and industry-specific advantages. It begins with a foundational overview of AI evolution, emphasizing how generative models such as GANs, VAEs, and Transformers have revolutionized language processing, image generation, and drug discovery. Prompt engineering is highlighted as a key methodology…
Read MoreImproved Candidate-Career Matching Using Comparative Semantic Resume Analysis
A resume is a prevalent and generally employed method for individuals to showcase their proficiency and qualifications. It is typically composed using diverse customized, personalized methods in multiple inconsistent formats (such as pdf, txt, doc, etc.). Screening candidates based on the alignment of their resume with a set of job requirements is typically a labori-…
Read MoreEmotion Mining from Speech in Collaborative Learning
Affective states, a dimension of attitude, have a critical role in the learning process. In the educational setting, affective states are commonly captured by self-report tools or based on sentiment analysis on asynchronous textual chats, discussions, or students’ journals. Drawbacks of such tools include: distracting the learning process, demanding time and commitment from students to…
Read MoreThe Design and Implementation of Intelligent English Learning Chabot based on Transfer Learning Technology
Chatbot operates task-oriented customer services in special and open domains at different mobile devices. Its related products such as knowledge base Question-Answer System also benefit daily activities. Chatbot functions generally include automatic speech recognition (ASR), natural language understanding (NLU), dialogue management (DM), natural language generation (NLG) and speech synthesis (SS). In this paper, we proposed…
Read MoreAn Alternative Approach for Thai Automatic Speech Recognition Based on the CNN-based Keyword Spotting with Real-World Application
An automatic speech recognition (ASR) is a key technology for preventing an ongoing global coronavirus epidemic. Due to the limited corpus database and the morphological diversity of the Thai language, Thai speech recognition is still difficult. In this research, the automatic speech recognition model was built differently from the traditional Thai NLP systems by using…
Read MoreChatbot Developments in The Business World
Chatbot is an application that is designed to help humans communicate with machines. NLP and API.AI are some of the components that are crucial in making chatbot as they help chatbot in performing chatting operations. Chatbot could be implemented in many aspects of life such as education, social media platforms, games, even in business. Business…
Read MoreEvaluating the Impact of Semantic Gaps on Estimating the Similarity using Arabic Wordnet
Knowledge-based approach is wield used in various NLP applications. For example, to evaluate the semantic similarity between words, the semantic evidence in lexical ontologies (wordnets) is commonly used. The success of the English WordNet (EnWN) in this domain has inspired the creation of several wordnets in different languages, including the Arabic WordNet (ArWN). The English…
Read MoreAdvances in Optimisation Algorithms and Techniques for Deep Learning
In the last decade, deep learning(DL) has witnessed excellent performances on a variety of problems, including speech recognition, object recognition, detection, and natural language processing (NLP) among many others. Of these applications, one common challenge is to obtain ideal parameters during the training of the deep neural networks (DNN). These typical parameters are obtained by…
Read MoreAn Integrated Framework for Pronominal Anaphora Resolution in Malayalam
Anaphora resolution is one of the old problems in Natural Language Processing. It is the process of identifying the antecedent of an anaphoric expression in a natural language text. Most of the NLP applications such as text summarization, question answering, information extraction, machine translation etc. require the successful resolution of anaphors. In this paper, we…
Read MoreChatting with Plants (Orchids) in Automated Smart Farming using IoT, Fuzzy Logic and Chatbot
Plants are living organisms that can hear and recognize the environment around them but cannot communicate to inform their needs. Thus, in the past, humans thought that it was impossible to communicate with plants. However, in this modern era, humans can be able to communicate with these plants. In this paper, we propose a model…
Read MoreSimulation-Optimisation of a Granularity Controlled Consumer Supply Network Using Genetic Algorithms
The decision support systems regarding the Supply Chains (SCs) management services can be significantly improved if an effective viable method is utilised. This paper presents a robust simulation optimisation approach (SOA) for the design and analysis of a granularity controlled and complex system known as Consumer Supply Network (CSN) incorporating uncertain demand and capacity. Minimising…
Read MoreDomain Independent Feature Extraction using Rule Based Approach
Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an…
Read MoreA Multilingual System for Cyberbullying Detection: Arabic Content Detection using Machine Learning
With the abundance of Internet and electronic devices bullying has moved its place from schools and backyards into cyberspace; to be now known as Cyberbullying. Cyberbullying is affecting a lot of children around the world, especially Arab countries. Thus concerns from cyberbullying are rising. A lot of research is ongoing with the purpose of diminishing…
Read MoreSolving the Capacitated Network Design Problem in Two Steps
In this paper, we propose a two steps-based algorithm to solve the modular link version of the Capacitated Network Design Problem (CNDP) which consists to determine the optimal network that guarantees the routing of a set of commodities. In our proposition, CNDP is divided into two sub-problems: Network Design problem (NDP) and Network Loading Problem…
Read MoreA Survey of Text Mining in Social Media: Facebook and Twitter Perspectives
Text mining has become one of the trendy fields that has been incorporated in several research fields such as computational linguistics, Information Retrieval (IR) and data mining. Natural Language Processing (NLP) techniques were used to extract knowledge from the textual text that is written by human beings. Text mining reads an unstructured form of data…
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