Implementation of a Chatbot System using AI and NLP

Lalwani, Tarun; Bhalotia, Shashank; Pal, Ashish; Rathod, Vasundhara; Bisen, Shreya

doi:10.2139/ssrn.3531782

Cited by 28 publications

(16 citation statements)

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“…For instance, chatbots in educational settings have been shown to improve student engagement and learning outcomes [19]. In healthcare, they are used for preliminary diagnosis and providing medical information [20].…”

Section: Chatbots and Virtual Assistantsmentioning

confidence: 99%

Artificial Intelligence Methods in Natural Language Processing: A Comprehensive Review

Chen,

Wang,

et al. 2024

HSET

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The rapid evolution of Artificial Intelligence (AI) since its inception in the mid-20th century has significantly influenced the field of Natural Language Processing (NLP), transforming it from a rule-based system to a dynamic and adaptive model capable of understanding the complexities of human language. This paper aims to offer a comprehensive review of the various applications and methodologies of AI in NLP, serving as a detailed guide for future research and practical applications. In the early sections, the paper elucidates the indispensable role of AI in NLP, highlighting its transition from symbolic reasoning to a focus on machine learning and deep learning, and its extensive applications in sectors such as healthcare, transportation, and finance. It emphasizes the symbiotic relationship between AI and NLP, facilitated by platforms like AllenNLP, which aid in the development of advanced language understanding models. Further, the paper explores specific AI techniques employed in NLP, including machine learning, Naive Bayes, and Support Vector Machines, and identifies pressing challenges and avenues for future research. It delves into the applications of AI in NLP, showcasing its transformative potential in tasks such as machine translation, facilitated by deep learning methods, and the development of chatbots and virtual assistants that have revolutionized human-technology interaction. The paper also highlights other fields impacted by AI techniques, including text summarization, sentiment analysis, and named entity recognition, emphasizing the efficiency and accuracy brought about by the integration of AI in these areas. In conclusion, the paper summarizes the remarkable advancements and persistent challenges in NLP, such as language ambiguity and contextual understanding, and underscores the need for diverse and representative labeled data for training. Looking forward, it identifies promising research avenues including Explainable AI, Few-shot and Zero-shot Learning, and the integration of NLP with other data modalities, aiming for a holistic understanding of multimodal data. The paper calls for enhanced robustness and security in NLP systems, especially in sensitive applications like content moderation and fake news detection, to foster trust and reliability in AI technologies. It advocates for continual learning in NLP models to adapt over time without losing previously acquired knowledge, paving the way for a future where AI and NLP work synergistically to understand and generate human language more effectively and efficiently.

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Section: Chatbots and Virtual Assistantsmentioning

confidence: 99%

Artificial Intelligence Methods in Natural Language Processing: A Comprehensive Review

Chen,

Wang,

et al. 2024

HSET

View full text Add to dashboard Cite

show abstract

“…NLP may be used in any field where AI is relevant, either by shortening statement processes or by analysing and refining data. Likewise, it is used in the travel industries and hospitality to provide outstanding customer service by using virtual assistants and chatbots to select hotels, book flights, and provide info about places to visit and experience, among other things, all of which is tailored to the traveller's preferences [35]. Similar NLP applications may be found in all areas where services are offered to consumers, such as optimising shows on TVs based on customer watching history or talking with portable chatbots nearly trip routes while driving, such as Google Maps [36].…”

Section: Nlp In Other Sectorsmentioning

confidence: 99%

Natural Language Processing Challenges and Issues: A Literature Review

Abro

Talpur

JUMANİ

2023

Gazi University Journal of Science

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Natural Language Processing (NLP) is the computerized approach to analysing text using both structured and unstructured data. NLP is a simple, empirically powerful, and reliable approach. It achieves state-of-the-art performance in language processing tasks like Semantic Search (SS), Machine Translation (MT), Text Summarization (TS), Sentiment Analyser (SA), Named Entity Recognition (NER) and Emotion Detection (ED). NLP is expected to be the technology of the future, based on current technology deployment and adoption. The primary question is: What does NLP have to offer in terms of reality, and what are the prospects? There are several problems to be addressed with this developing method, as it must be compatible with future technology. In this paper, the benefits, challenges and limitations of this innovative paradigm along with the areas open to do research are shown.

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“…This section mentions the related similar chatbot systems that are used in various domains. The authors in [6] proposed a chatbot called Eliza. In 1966, Eliza was developed, who appeared ready to deceive consumers into believing they were conversing with a real person.…”

Section: Related Workmentioning

confidence: 99%

An Interactive Chatbot for College Enquiry

Hassan¹,

Elsayed

2023

Journal of Computing and Communication

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Chatbots are now widely used in many applications, particularly in systems that give intelligent support to users. In many situations, these systems are equipped with Chatbots that can read user requests and offer the appropriate replies in a timely and accurate manner. This paper presents a Chatbot system in an educational domain. A system was created to assist university students in their inquiries. The primary goal was to develop a specific architecture, create a model for managing communication, and provide the proper responses to the students. For this purpose, a system has been developed to recognize queries and provide answers to students using artificial intelligence techniques and natural language processing. Finally, an experimental campaign was run when the planned model was implemented to verify its enforceability and efficiency.

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Implementation of a Chatbot System using AI and NLP

Cited by 28 publications

References 1 publication

Artificial Intelligence Methods in Natural Language Processing: A Comprehensive Review

Artificial Intelligence Methods in Natural Language Processing: A Comprehensive Review

Natural Language Processing Challenges and Issues: A Literature Review

An Interactive Chatbot for College Enquiry

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