..., often struggle with unstructured, dynamic, and context-rich information. AI technologies, particularly machine learning (ML), natural language processing (NLP), expert systems, robotic process automation (RPA), recommendation engines, and knowledge graphs, are transforming KM into an intelligent...

... in improving customer satisfaction in the tourism and hospitality industries in emerging economies. Artificial Intelligence tourism and hospitality customer experience natural language processing BERT model Introduction The tourism and hospitality sectors are among the biggest and fastest-growing sectors...

... focused on growth, resilience, and competitive advantage. This shows that business transformations are bound to occur, what is challenging is to accept, assimilate, and change. 1. Introduction Artificial intelligence machine learning AI-driven tools natural language processing predictive analytics...

... encompasses research on survey recruitment, and other applications of LinkedIn data in accounting studies. Social media LinkedIn professional connections, experience, and skills ESG reporting machine learning natural language processing ...

... of artificial intelligence systems is to solve complex problems using human logic and reasoning. One such revolutionary field of AI that can comprehend, interpret, and interact with human language is Natural Language Processing (NLP). Over the years, NLP has advanced a lot from analyzing online textual reviews...

... such as ensuring recognition and referencing the replies supplied by ChatGPT. ChatGPT artificial intelligence chatbot OpenAI natural language processing Introduction ChatGPT has recently become one of the most popular tools for conversational AI. It is an artificial intelligence natural language processing...

... the influence of more specific AI implementation strategies on Islamic conformance and operational efficacy in the context of IF. Artificial Intelligence IF financial management technology integration big data natural language processing Introduction The contemporary financial era presents significant...

.... By leveraging natural language processing (NLP) and machine learning (ML), these chatbots can provide customised support to customers with personalised responses to modernise the customer service procedure and improve the customers’ overall experience. The present research explores the role of AI-powered...

... their resources more effectively. We elaborate throughout this text how AI, in particular by using methods such as natural language processing, generative adversarial networks (GANs) and other related techniques, can be understood as what we have termed ‘Explainable AI’ to address operational issues in the modern...

... and sustainability. The human–machine collaboration emphasized by Industry 5.0 will necessitate the reshaping of workforce skillsets and operational approaches. Industry 5.0 digital twin artificial intelligence natural language processing collaborative robots Nvidia Blackwell Nvidia Isaac Nvidia Omniverse...

... job descriptions by linking the skills sought by employers to a dictionary of Big Five personalities via the keyword extraction technique of Term Frequency – Inverse Document Frequency (TFIDF), a Natural Language Processing (NLP) technique. Vectorizing the personality references from job descriptions...

... board skills dynamics skills taxonomy natural language processing Introduction Major transformative phenomena, such as technological progress and trade, are shaping labor markets. Skills are an important factor in this process as they significantly influence how labor market transformations affect...

... theory of education and critical thinking ( Gunduzalp, 2024 ). Conclusion The amalgamation of digital game-based learning with artificial intelligence-powered natural language processing holds immense promise for enriching inquiry-based teaching methods in science education. This review underscores...

... [AI] applications. AI can be very beneficial in classifying artefacts automatically through machine learning [ML] and natural language processing [NLP]. For example, an algorithm can identify the source and age of artefacts based on an image and can do this much faster for a large collection of photos...

..., and the available quantity of data has increased dramatically. Artificial intelligence machine learning supervised learning reinforcement learning natural language processing deep learning 6.1 Introduction Our everyday lives rely heavily on technology, and we use various forms of technology in every...

... natural language processing causal inference Introduction Listening to and understanding one's customers has been a cornerstone of marketing. Consequently, these goals have long informed business strategies, responses, and resource allocation. By extension, research centered...

... text data is a nontrivial task. In this chapter, we review established natural language processing (NLP) methods for traditional tasks (e.g., LDA for topic modeling and lexicons for sentiment analysis and writing style extraction) and provide an outlook into the future of NLP in marketing, covering...

... to a focal audience. Natural language processing (NLP) techniques are suited to this end. Such techniques help identify which issues firm members and audiences prioritize in written texts ( Corritore, Goldberg, & Srivastava, 2020 ; Grimmer, 2010 ). They are also able to leverage observed word...

... prediction machine learning deep learning computer vision natural language processing Introduction For over 100 years, the Artificial Intelligence (AI) umbrella has extended to include the most advanced technologies of each time period. Research in AI has been scattered across disciplines with a few...

... from full texts, intros, song and album titles to band names, pseudonyms, and literary quotations. This chapter sheds light on heavy metal's fascination with the history and ‘arcane’ sound of Latin, and investigates its patterns of use in lyrics with the help of Natural Language Processing tools...