Open Access Theses and Dissertations

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KTH

1. Rinnarv, Jonathan. GANChat : A Generative Adversarial Network approach for chat bot learning.

Degree: Electrical Engineering and Computer Science (EECS), 2020, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278143 

Recently a new method for training generative neural networks called Generative Adversarial Networks (GAN) has shown great results in the computer vision domain and shown potential in other generative machine learning tasks as well. GAN training is an adversarial training method where two neural networks compete and attempt to outperform each other, and in the process they both learn. In this thesis the effectiveness of GAN training is tested on conversational agents also called chat bots. To test this, current state-of-the-art training methods such as Maximum Likelihood Estimation (MLE) models are compared with GAN method trained models. Model performance was measured by closeness of the model distribution from the target distribution after training. This thesis shows that the GAN method performs worse the MLE in some scenarios but can outperform MLE in some cases.

Nyligen har en ny metod för att träna generativa neurala nätverk kallad Generative Adversarial Networks (GAN) visat bra resultat inom datorseendedomänen och visat potential inom andra maskininlärningsområden också GAN-träning är en träningsmetod där två neurala nätverk tävlar och försöker överträffa varandra, och i processen lär sig båda. I detta examensarbete har effektiviteten av GAN-träning testats på konversationsagenter, som också kallas Chat bots. För att testa det här jämfördes modeller tränade med nuvarande state-of- the-art träningsmetoder, så som Maximum likelihood-metoden (ML), med GAN-tränade modeller. Modellernas prestation mättes genom distans från modelldistribution till måldistribution efter träning. Det här examensarbetet visar att GAN-metoden presterar sämre än ML-metoden i vissa scenarier men kan överträffa ML i vissa fall.

Subjects/Keywords: Computer science Machine learning GAN chat bot; Computer Sciences; Datavetenskap (datalogi)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rinnarv, J. (2020). GANChat : A Generative Adversarial Network approach for chat bot learning. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278143

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rinnarv, Jonathan. “GANChat : A Generative Adversarial Network approach for chat bot learning.” 2020. Thesis, KTH. Accessed February 28, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278143.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rinnarv, Jonathan. “GANChat : A Generative Adversarial Network approach for chat bot learning.” 2020. Web. 28 Feb 2021.

Vancouver:

Rinnarv J. GANChat : A Generative Adversarial Network approach for chat bot learning. [Internet] [Thesis]. KTH; 2020. [cited 2021 Feb 28]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278143.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rinnarv J. GANChat : A Generative Adversarial Network approach for chat bot learning. [Thesis]. KTH; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278143

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Linnaeus University

2. Strutynskiy, Maksym. A concept of an intent-based contextual chat-bot with capabilities for continual learning.

Degree: computer science and media technology (CM), 2020, Linnaeus University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99102 

Chat-bots are computer programs designed to conduct textual or audible conversations with a single user. The job of a chat-bot is to be able to find the best response for any request the user issues. The best response is considered to answer the question and contain relevant information while following grammatical and lexical rules. Modern chat-bots often have trouble accomplishing all these tasks. State-of-the-art approaches, such as deep learning, and large datasets help chat-bots tackle this problem better. While there is a number of different approaches that can be applied for different kind of bots, datasets of suitable size are not always available. In this work, we introduce and evaluate a method of expanding the size of datasets. This will allow chat-bots, in combination with a good learning algorithm, to achieve higher precision while handling their tasks. The expansion method uses the continual learning approach that allows the bot to expand its own dataset while holding conversations with its users. In this work we test continual learning with IBM Watson Assistant chat-bot as well as a custom case study chat-bot implementation. We conduct the testing using a smaller and a larger datasets to find out if continual learning stays effective as the dataset size increases. The results show that the more conversations the chat-bot holds, the better it gets at guessing the intent of the user. They also show that continual learning works well for larger and smaller datasets, but the effect depends on the specifics of the chat-bot implementation. While continual learning makes good results better, it also turns bad results into worse ones, thus the chat-bot should be manually calibrated should the precision of the original results, measured before the expansion, decrease.

Subjects/Keywords: Machine learning; intent based; chat-bot; dialogue systems; rule based; Python; TensorFlow; TFLearn; continual learning; online learning; supervised learning; unsupervised learning; IBM Watson; Watson Assistant; Computer Sciences; Datavetenskap (datalogi)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Strutynskiy, M. (2020). A concept of an intent-based contextual chat-bot with capabilities for continual learning. (Thesis). Linnaeus University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99102

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Strutynskiy, Maksym. “A concept of an intent-based contextual chat-bot with capabilities for continual learning.” 2020. Thesis, Linnaeus University. Accessed February 28, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99102.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Strutynskiy, Maksym. “A concept of an intent-based contextual chat-bot with capabilities for continual learning.” 2020. Web. 28 Feb 2021.

Vancouver:

Strutynskiy M. A concept of an intent-based contextual chat-bot with capabilities for continual learning. [Internet] [Thesis]. Linnaeus University; 2020. [cited 2021 Feb 28]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99102.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Strutynskiy M. A concept of an intent-based contextual chat-bot with capabilities for continual learning. [Thesis]. Linnaeus University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-99102

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

3. Chovanec, Tomáš. Rezervace vstupenek pomocí botů na chatovacích platformách: Chat Bot Based Ticket Reservation.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/69875 

Today, people are starting to get familiar with the term of chat bots and it makes nodifference if they are specialists or general public. The aim of this thesis is to define chat botsas a web service, describe platforms which use this service and try to develop a connectionfor advanced functions, for example online payment gateways or virtual assistants, to extendcurrent ticket booking chat bot services. Advisors/Committee Members: Pluskal, Jan (advisor), Lichtner, Ondrej (referee).

Subjects/Keywords: chat bot; Microsoft Bot Framework; proces rezervácie vstupeniek; inteligentný asistent; Cortana; platobná brána; PayPal; internetový kalendár; Google Calendar; kognitívne rozpoznávanie; chat bot; Microsoft Bot Framework; ticket reservation; virtual assistant; Cortana; onlinepayment solutions; PayPal; calendar services; Google Calendar; cognitive recognition

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❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chovanec, T. (2019). Rezervace vstupenek pomocí botů na chatovacích platformách: Chat Bot Based Ticket Reservation. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/69875

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chovanec, Tomáš. “Rezervace vstupenek pomocí botů na chatovacích platformách: Chat Bot Based Ticket Reservation.” 2019. Thesis, Brno University of Technology. Accessed February 28, 2021. http://hdl.handle.net/11012/69875.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chovanec, Tomáš. “Rezervace vstupenek pomocí botů na chatovacích platformách: Chat Bot Based Ticket Reservation.” 2019. Web. 28 Feb 2021.

Vancouver:

Chovanec T. Rezervace vstupenek pomocí botů na chatovacích platformách: Chat Bot Based Ticket Reservation. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/11012/69875.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chovanec T. Rezervace vstupenek pomocí botů na chatovacích platformách: Chat Bot Based Ticket Reservation. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/69875

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.