A Chatbot Framework for Yioop

Over the past few years, messaging applications have become more popular than Social networking sites. Instead of using a specific application or website to access some service, chatbots are created on messaging platforms to allow users to interact with companies’ products and also give assistance as needed. In this project, we designed and implemented a chatbot Framework for Yioop. The goal of the Chatbot Framework for Yioop project is to provide a platform for developers in Yioop to build and deploy chatbot applications. A chatbot is a web service that can converse with users using artificial intelligence in messaging platforms. Chatbots feel more like a human and it changes the interaction between people and computers. The Chatbot Framework enables developers to create chatbots and allows users to connect with them in the user chosen Yioop discussion channel. A developer can incorporate language skills within a chatbot by creating a knowledge base so that the chatbot understands user messages and reacts to them like a human. A knowledge base is created by using a language understanding web interface in Yioop

Artificial Intelligence for the Financial Services Industry: What Challenges Organizations to Succeed?

As a research field, artificial intelligence (AI) exists for several years. More recently, technological breakthroughs, coupled with the fast availability of data, have brought AI closer to commercial use. Internet giants such as Google, Amazon, Apple or Facebook invest significantly into AI, thereby underlining its relevance for business models worldwide. For the highly data driven finance industry, AI is of intensive interest within pilot projects, still, few AI applications have been implemented so far. This study analyzes drivers and inhibitors of a successful AI application in the finance industry based on panel data comprising 22 semi-structured interviews with experts in AI in finance. As theoretical lens, we structured our results using the TOE framework. Guidelines for applying AI successfully reveal AI-specific role models and process competencies as crucial, before trained algorithms will have reached a quality level on which AI applications will operate without human intervention and moral concerns

Conversational Agent: Developing a Model for Intelligent Agents with Transient Emotional States

The inclusion of human characteristics (i.e., emotions, personality) within an intelligent agent can often increase the effectiveness of information delivery and retrieval. Chat-bots offer a plethora of benefits within an eclectic range of disciplines (e.g., education, medicine, clinical and mental health). Hence, chatbots offer an effective way to observe, assess, and evaluate human communication patterns. Current research aims to develop a computational model for conversational agents with an emotional component to be applied to the army leadership training program that will allow for the examination of interpersonal skills in future research. Overall, the current research explores the application of the deep learning algorithm to the development of a generalized framework that will be based upon modeling empathetic conversation between an intelligent conversational agent (chatbot) and a human user in order to allow for higher level observation of interpersonal communication skills. Preliminary results demonstrate the promising potential of the seq2seq technique (e.g., through the use of Dialog Flow Chatbot platform) when applied to emotion-oriented conversational tasks. Both the classification and generative conversational modeling tasks demonstrate the promising potential of the current research for representing human to agent dialogue. However, this implementation may be extended by utilizing, a larger more high-quality dataset

AN OVERVIEW OF CHATBOTS USAGE IN RECRUITMENT AND SELECTION PRACTICES

Artificial Intelligence (AI) has affected different functions of businesses including Human Resources, and particularly, recruitment processes. With Chatbots (conversational agents) systems in place, HR can perform tasks like identifying, selecting, and interviewing talented candidates quickly and efficiently. This study offers an overview of the current state of chatbots usage in recruitment and selection processes. For doing this, we performed a literature review. We have retrieved academic articles from Scopus and Web of Science until March 2022. Also, we complemented the information retrieved with several searches on Google so as to find interesting grey literature and information. First, we define a chatbot and discuss its technical and social requirements. Second, we explain how chatbots are currently used in R&S processes in organizations, their benefits and their cons. By doing this, we seek to give AI and NLP developers valuable insights when creating chatbots for recruiting objectives

How chatbots are used in recruitment and selection practices?

In the modern era, Artificial Intelligence (AI) has affected different functions of businesses, including Human Resources, in recruitment processes. With Chatbots (conversational agents) systems in place, HR can perform tasks like identifying, selecting, and interviewing talented candidates with more speed and consequently focus on strategic goals more effectively. This study aims to assess the current state of chatbot usage in HR processes in organisations, particularly in Higher Education Institutions (HEIs). For Part Ⅰ, the chatbot’s role is evaluated in detail for each stage of recruitment (i.e., sourcing, screening, selection and onboarding of candidates). Moreover, we will discuss how chatbot providers develop this service in terms of needed technical technologies and communicational aspects. The findings will help identify the best practices in developing better chatbots that align with the demands of modern hiring. In addition, we investigate chatbots’ impact on higher education with the rise of online learning and the Covid-19 pandemic. In part two, we develop a chatbot using the Google DialogFlow platform to support the admission process for prospective PhD students in the Doctoral Management Program of the UPC. This FAQ bot will be implemented as a supplementary channel in the doctoral program website to understand students’ queries and provide predefined answers. A survey is conducted based on the TAM framework to assess the chatbot’s functionality, quality, and intention of use. Based on the responses and findings, we will discuss how chatbots are a viable option to create new innovative services that are helpful for both candidates and educators. In the end, based on lessons learned, we propose conclusions, discussion and several recommendations for these intelligent systems. It is hoped that this work will open up new research possibilities for future optimisations in the fields of chatbots and recruitment in the future.En la era moderna, la Inteligencia Artificial (IA) ha afectado a diferentes funciones de las empresas, incluida la de Recursos Humanos, en los procesos de contratación. Con los sistemas de Chatbots (agentes conversacionales) implementados, HR puede realiza r tareas como identificar, seleccionar y entrevistar a personas candidat as talentos a s con más velocidad y, en consecuencia, enfocarse en objetivos estratégicos de manera más efectiva. Este estudio tiene como objetivo evaluar el estado actual del uso de chatbots en los procesos de recursos humanos en las organizaciones, particularmente en las Instituciones de Educación Superior (IES). Para la Parte Ⅰ, el rol del chatbot se evalúa en detalle para cada etapa del reclutamiento (i.e., planificación, abastecimiento, selec ción, verificación de referencias, selección e incorporación de candidatos). Además, discutiremos cómo los proveedores de chatbots desarrollan este servicio en términos de tecnologías técnicas necesarias y aspectos de comunicación. Los hallazgos ayudarán a identificar las mejores prácticas para desarrollar mejores chatbots que se alineen con las demandas de la contratación moderna. Además, investigamos el impacto de los chatbots en la educación superior con el aumento del aprendizaje en línea y la pandemia de Covid19. En la segunda parte, desarrollamos un chatbot utilizando la plataforma Google DialogFlow para apoyar el proceso de admisión de futuros estudiantes de doctorado Doctorado de la UPC. Este bot de preguntas en el Programa de Gestión de frecuentes se implementará como un canal complementario en el sitio web del programa de doctorado para comprender las consultas de los estudiantes y proporcionar respuestas predefinidas. Se realiza una encuesta basada en el marco TAM para evaluar la funcio nalidad, la calidad y la intención de uso del chatbot. Según las respuestas y los hallazgos, analizaremos cómo los chatbots son una opción viable para crear nuevos servicios innovadores que sean útiles tanto para los personas como para los educadores. Al candidat as final, en base a las lecciones aprendidas, proponemos conclusiones, discusión y varias recomendaciones para estos sistemas inteligentes. Se espera que este trabajo abra nuevas posibilidades de investigación para futuras optimizaciones en los campos de los chatbots y el reclutamiento en el futur