Seminar chatbots and conversational agents
-
Teaching
Details
Faculty Faculty of Science and Medicine Domain Computer Science Code UE-SIN.07822 Languages English Type of lesson Seminar
Level Master Semester AS-2022 Schedules and rooms
Struct. of the schedule 2h par semaine durant 14 semaines Contact's hours 28 Teaching
Responsibles - Cudré-Mauroux Philippe
Teachers - Abou Khaled Omar
- Cudré-Mauroux Philippe
- Mugellini Elena
Description Nowadays, chatbots (or conversational agents) are available on different platforms. It can be in a professional context (Skype, Slack) or a private one (Facebook Messenger, Discord, Telegram). Since Facebook's F8 2016 conference, these bots have become more democratic and have flooded the different platforms. They tend to replace mobile applications for their ease of use and various functionalities. In addition, there is no need to install them because they are available on apps that everyone already has.
Different uses stand out. For example, it is a way for brands to automatically answer questions from users (support, after-sales service). These bots can work as assistants for different tasks (make appointments, various automations, reminders). Online stores use it to allow people to place orders as if talking to a person. The news sites use them to distribute a summary of the articles of the day.
Thanks to the outstanding evolutions in artificial intelligence in the last decade, it is now possible to converse in a more or less natural way with bots.
This seminar focuses on investigating approaches and technologies used in today's chatbots. There are different types of bot for different uses. The techniques and technologies used vary according to the use of the bot in question. It is then worthwhile to understand the advantages and disadvantages of each of these techniques. All bots are not powered by machine learning, some are rule-based. Natural language understanding as well as natural language generation are two fundamental aspects of chatbots.Monitoring a context in a conversation is also a very important element. Analyzing and designing a human-machine interface is not an easy task. Bots can have moods and a personality. All these aspects must be considered while designing a chatbot.
A particular emphasis this year will be given to chatbots related to health and nutrition (e.g. nutritional coach, cook assistant, advisor for food related questions, recipes creator and so on).
The seminar will have a strong practical component as students will investigate existing chatbots as well as develop new concepts in the aforementioned domains.Training objectives - Identify and describe existing approaches and mechanisms for designing chatbots
- Identify the main components of a chatbot architecture
- Discuss and compare the different techniques available for chatbots with their strengths and weaknesses
- compare and Identify the best technological solution to design a specific type of chatbot
- Understand the techniques used to follow the context in a conversation
- Know the landscape of existing bots in the nutrition domain
- Evaluate the capabilities and skills of a botComments MSc-CS BENEFRI - (Code Ue:33503 / Track: T3, Code Ue: 63503/ Track: T6). The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/.
Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/
Softskills No Off field No BeNeFri Yes Mobility Yes UniPop No -
Assessments methods
Evaluation continue
Assessments methods By rating -
Assignment
Valid for the following curricula: Additional Courses in Sciences
Version: ens_compl_sciences
Paquet indépendant des branches > Specialized courses in Computer Science (Master level)
Additional programme requirements for PhD studies [PRE-DOC]
Version: 2020_1/v_01
Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Computer Science (Master level)
Bioinformatics [3e cycle]
Version: 2024_2/V_01
Continuing education > Specialized courses in Computer Science (Master level)
Computer Science [3e cycle]
Version: 2024_2/V_01
Continuing education > Specialized courses in Computer Science (Master level)
Computer Science [POST-DOC]
Version: 2015_1/V_01
Continuing education > Specialized courses in Computer Science (Master level)
MSc in Computer science (BeNeFri)
Version: 2023_1/V_01
MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T3 : Visual ComputingMSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T6: Data Science