An e-business chatbot using AIML and LSA

Thomas, Neethu

doi:10.1109/icacci.2016.7732476

Cited by 82 publications

(28 citation statements)

References 3 publications

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“…Entre las ventajas de AIML, se encuentra el hecho de que muchos archivos AIML con diferentes áreas de conocimiento y de conversación se pueden combinar en un corpus para mejorar la escalabilidad y compatibilidad del sistema. Entre sus desventajas está el hecho de que el desarrollador tiene que escribir los patrones para todos los inputs que el sistema puede recibir (Thomas, 2016), lo que puede ser una tarea complicada.…”

Section: Tecnología Del Chatbot: El Formato Aiml En Breveunclassified

Perpectivas de las tecnologías de Chatbot y su aplicación a las entrevistas de evaluación del lenguaje

Miguel¹,

Cabrera²

2020

Pragmalinguistica

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Section: Tecnología Del Chatbot: El Formato Aiml En Breveunclassified

Perpectivas de las tecnologías de Chatbot y su aplicación a las entrevistas de evaluación del lenguaje

Miguel¹,

Cabrera²

2020

Pragmalinguistica

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“…Weizenbaum J et al presented a chatbot ELIZA and the mental issues faced with the system is described [1]. Thomas et al presented a route direction bot for showing way in a single layout [2]. Rashmi et al implemented a inquisitive chatbot for providing addresses for a complex queries.…”

Section: Literature Surveymentioning

confidence: 99%

Design a Chatbot for Chennai Corporation Using Logistic Regression Algorithm

2019

IJRTE

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Chatbots are the famous nowadays in business because of its service offered to the community at large. They provide support of 24*7 for business in terms of customercare, helpline, planning, analyzing and decision making. In this paper, a chatbot for Chennai corporation is proposed. This chatbot helps the citizens in providing the responses for their queries related to civic problems. There is no such system is available to handle the public grievances automatically. This system handles the public query and the relevant suggestion and responses will be given promptly. The chatbot receives the text or voice input and processed. The voice recognition module used to recognize the voice query and the voice to text convertor used to convert the voice data into text format. The matchmaking process used to match the input query with the available data set and the relevant responses is generated. If no match is for the query, the matchmaker will find the relevant response from online sources. The output channel equipped with the text to voice converter which converts the text data into voice and it will be delivered to the end user. The naïve bayers and logistic regression algorithm is implemented for classifying the query and the performance is compared. The result shows that the logistic regression algorithm outperform well with the precision and recall values.

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“…N T Thomas [42] Text Proposed a chatbot for an E-business purposes which automatically gives immediate response to the user based on the data sets of FAQs using Artificial Intelligence Markup Language (AIML) and Latent Semantic Analysis (LSA).…”

Section: Inputs Significance Applicationmentioning

confidence: 99%

Various Real Time Chat Bots and Their Applications in Human Life

Sree*,

Sahitya,

Kaushik

et al. 2019

IJRTE

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Chatbots are also referred to as virtual assistance devices. They are the basic forms of artificial intelligence software that can imitate human conversations. Chatbots are relatively a new technology. The main goal of this survey paper is to provide the information about the various existing chatbots and their history of evaluation, and the applications of various chatbots in different domains. Chatbots are applied in fields like medical, E-commerce, business, education, banking, customer services, entertainment, etc. Chatbots cab be analyzed and improved. Main goal of any chatbot is to allow the user to make a natural conversation with machine. A conversational system consists of dialogue management, speech recognition, speech synthesis and conversation generation.

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An e-business chatbot using AIML and LSA

Cited by 82 publications

References 3 publications

Perpectivas de las tecnologías de Chatbot y su aplicación a las entrevistas de evaluación del lenguaje

Perpectivas de las tecnologías de Chatbot y su aplicación a las entrevistas de evaluación del lenguaje

Design a Chatbot for Chennai Corporation Using Logistic Regression Algorithm

Various Real Time Chat Bots and Their Applications in Human Life

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