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wiki:software:beuthbot:berichte:ws2019:zwischen
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Inhaltsverzeichnis
Interim Report to the Master Project WS 2019/20 | Zwischenbericht zum Masterprojekt WS 2019/20
Introduction / Summary
Motivation
A large number of companies are renewing their customer service in order to quickly bring their range of offers to potential buyers. Digitalization is a useful tool for bringing information to interested parties. The chatbot plays an important role here. Chatbots are dialogue systems that communicate via voice or text messages. Chatbots are used in various areas and present a variety of offers to inform users. There are also other categories, such as chatbots, which provide specific information about the weather. The Beuth University of Applied Sciences in Berlin offers its students, employees, scientific staff and teachers various services. The focus is on important questions such as when the opening hours of Beuth University are. For students, the opening hours of the library, the study administration, the dean's offices, the study and recreation rooms are also important. For these reasons Professor Thomas Ziemer proposes to develop a chatbot for the university.
Target group
The chatbot is aimed primarily at students, teachers and visitors to Beuth University. It helps the above mentioned groups to quickly get information about the learning rooms, Mensaplan and other services of the university. The chatbot also provides information about the weather.
Scope
Beuth University has an interest in offering a service that leads through the university. This service is intended to help new students find their way around Beuth University. This includes, among other things, that students have knowledge of exam dates and the teaching staff's consultation hours in order to better organize their studies. The chatbot also answers questions about the Mensaplan. The Mensa's offer is varied, e.g. the Chatbot answers to inquiries, when there is vegetarian or vegan food. It has other functions as well: So it can answer questions about the next week's menu and can consider hints from users, such as the request of a vegetarian.
Software Architecture
Table of content
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Overview
BeuthBot consists of many interwoven Microservices. Evey Microservice uses our basic API to communicate with other Microservices. This approach enables us to change parts of the system easily at any time or to introduce new Microservices, all they need to do is to implement our API.
Basic Structure
Our application is basically composed of the following four components.
Bot ⇔ Gateway ⇔ Registry ⇔ ServiceFollowing diagram shows that in more detail:
A user can write the Bot to request informations, the meaning of the message is extracted and a fitting Microservice is choosen to retrieve the necessary data. A response is build from that data and distributed back up to the bot which answers the users request.
Following sequence diagram further illustrates that:
Bot
This is an abstraction for the available chatbots, e.g. a Bot for Telegram and another Bot for WhatsApp.
The user interacts with this Microservice, here she can request information and gets answers from BeuthBot.
Gateway
The Gateway is the centerpiece of BeuthBot one could say.
The Bot notifies the Gateway with the message it got from the user.
The Gateway then uses NLP (Natural Language Processing) Microservices to get the meaning and intention of the user. Here we try to extract what the user wants from BeuthBot, to notify the right service and present a fitting answer to our user.
Registry
After obtaining the intention of our user, the Gateway notifies the Registry, to get the information the user requested.
The Registry distributes the request to the correct Service, that takes care of retrieving the right informations.
Service
Service is an abstraction for the implemented Microservices that retrieve the necessary data we need to answer users requests. E.g. the MensaService is a Microservice that can give informations about the current menu, filtered by a number of parameters, e.g. a vegan user.
API
Because of the complexity of the single Microservices, every single Microservice implements its own, distinct, API.
But to answer a users request we use a unified, comprehensive API. Its basic idea is to pass a Response-Object trough the individual Microservices, which consists of the initial request, an answer as a response to the users request and informations about the user.
Following class diagram further illustrates that:
wiki/software/beuthbot/berichte/ws2019/zwischen.1576069307.txt.gz · Zuletzt geändert: 11.12.2019 14:01 von Christopher Lehmann