Chatbot and bullyfree Chat

Saranya, S; Chidida, K; R, Abarna.

doi:10.1109/icscan.2019.8878779

Cited by 11 publications

(3 citation statements)

References 1 publication

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“…Leveraging natural language processing and machine learning, chatbots emerge as indispensable tools for enhancing consumer engagement and corporate productivity [16]. This literature review underscores the transformative potential of chatbots in revolutionizing agricultural practices [17].…”

Section: Literature Reviewmentioning

confidence: 99%

FarmTechBot (FTB): Empowering farmers for better harvest

G. Kalaiselvi,

B. Rubavarshini,

T. Thirumullai

et al. 2024

Int. J. Sci. Res. Arch.

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In an evolving world, the FarmTechBot (FTB) emerges as a pioneering digital assistant, empowering farmers with essential insights and real-time information crucial for optimizing agricultural practices. The presence of chatbot functionality capable of addressing queries related to soil, pest, and market linkage associates to overcome hurdles for users seeking real-time information. Furthermore, the lack of voice recognition capabilities limits accessibility, especially for users who prefer or require voice-based interaction. Additionally, the manual process of pest identification from uploaded crop images hampers efficiency, prolonging the time required for pest management. The FTB represents a significant advancement in agricultural technology, addressing the existing system's limitations and empowering farmers with real-time information, enhanced accessibility, and streamlined pest management capabilities. The FTB utilizes a combination of techniques including Histogram of Oriented Gradients (HOG) for image feature extraction and classification using Support Vector Classifier (SVC). In Natural Language Processing (NLP), it employs tokenization and TF-IDF vectorization for text preprocessing and representation, alongside Linear Support Vector Classifier (LinearSVC) for intent classification.

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Section: Literature Reviewmentioning

confidence: 99%

FarmTechBot (FTB): Empowering farmers for better harvest

G. Kalaiselvi,

B. Rubavarshini,

T. Thirumullai

et al. 2024

Int. J. Sci. Res. Arch.

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show abstract

“…This study explores the use of chatbots for business purposes. It discusses the potential benefits of chatbots in enhancing customer service, improving customer satisfaction, and serving as alternative touchpoints for businesses [95]. and it also emphasizes the integration of emotion management in chatbots, highlighting how machine learning technologies can improve interaction and overall user experience [137], which could appropriately be examples of key studies.…”

Section: Literature Search and Selectionmentioning

confidence: 99%

Evolving Conversations: A Review of Chatbots and Implications in Natural Language Processing for Cultural Heritage Ecosystems

Suryanto,

Wibawa,

Hariyono

et al. 2023

IJRCS

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Chatbot technology, a rapidly growing field, uses Natural Language Processing (NLP) methodologies to create conversational AI bots. Contextual understanding is essential for chatbots to provide meaningful interactions. Still, to date chatbots often struggle to accurately interpret user input due to the complexity of natural language and diverse fields, hence the need for a Systematic Literature Review (SLR) to investigate the motivation behind the creation of chatbots, their development procedures and methods, notable achievements, challenges and emerging trends. Through the application of the PRISMA method, this paper contributes to revealing the rapid and dynamic progress in chatbot technology with NLP learning models, enabling sophisticated and human-like interactions on the trends observed in chatbots over the past decade. The results, from various fields such as healthcare, organization and business, virtual personalities, to education, do not rule out the possibility of being developed in other fields such as chatbots for cultural preservation while suggesting the need for supervision in the aspects of language comprehension bias and ethics of chatbot users. In the end, the insights gained from SLR have the potential to contribute significantly to the advancement of chatbots on NLP as a comprehensive field.

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“…In this paper "Chatbot and bully free chat" [1].The assistance of AI calculation the chatbot is developed utilizing Normal Language Processing for preparing the bot and to make up the bot act in a correct manner, with the goal that the preparation and testing should be possible utilizing AI calculation. This procedure is utilized in Educational institute, when the client pose an inquiry, the bot will break the sentence into words and check for the specific bully word and afterward begins responding to the given inquiries if it finds the bully words, then it mentions the bully word.…”

Section: Related Workmentioning

confidence: 99%

Health Care Chatbot Assistant System

ADARSH H J,

Bhaskar Reddy P.V,

Suhasini S Hosamani

et al. 2023

J. Adv. Zool.

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Rasa stack consists of many open source AI apparatuses solely utilized in plan to make a logical chatbot. It consists of incredible APIs embedded along the Rasa stack that incorporates Natural language understanding. It incorporates the sack of words calculation helping in streamlining portrayl utilized in measurable displaying and AI stages and furthermore trend setting innovation. The proposed framework is to make an option in contrast to this ordinary strategy for visiting a clinic and making a meeting with a specialist to get analysis. From the user queries chatbot will, predicts the infection and prescribes treatment along with necessary medicine. It like wise support the utilization of this RASA stage for the client specific format according to their prerequisites and furthermore elevates in building up the system for better efficiency.

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Chatbot and bullyfree Chat

Cited by 11 publications

References 1 publication

FarmTechBot (FTB): Empowering farmers for better harvest

FarmTechBot (FTB): Empowering farmers for better harvest

Evolving Conversations: A Review of Chatbots and Implications in Natural Language Processing for Cultural Heritage Ecosystems

Health Care Chatbot Assistant System

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