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Mobile Application for Presentation of Anime World Information
Odehnal, Jiří ; Rudnitckaia, Julia (referee) ; Hynek, Jiří (advisor)
This bachelor thesis deals with the design and development of a mobile application for Android platform as an extension of the existing Happo.cz web service. The aim of the work is to implement a simple and user-friendly user interface that provides basic information about animated films. The application should also support friendly relationships between users and encourage their mutual communication. Part of the thesis is also implementation of the server part and the content recommendation system.
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Deep Book Recommendation
Gráca, Martin ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This thesis deals with the field of Recommendation systems using Deep Neural Networks and their use in book recommendation. There are the main traditional recommender systems analysed and their representations are summarized, as well as systems with more advancec techniques based on machine learning.. The core of the thesis is the use of convolutional neural networks for natural language processing and the creation of a book recommendation system. Suggested system make recommendation based on user data, including user reviews and book data, including full texts.
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Deep Book Recommendation
Gráca, Martin ; Kolář, Martin (referee) ; Hradiš, Michal (advisor)
This thesis deals with the field of recommendation systems using deep neural networks and their use in book recommendation. There are the main traditional recommender systems analysed and their representations are summarized, as well as systems with more advanced techniques based on machine learning. The core of the thesis is to use convolutional neural networks for natural language processing and create a hybrid book recommendation system. Suggested system includes matrix factorization and make recommendation based on user ratings and book metadata, including texts descriptions. I designed two models, one with bag-of-words technique and one with convolutional neural network. Both of them defeat baseline methods. On the created data set, that was created from the Goodreads, model with CNN beats model with BOW.
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Prediction of Shopper Behaviour
Kačo, Adam ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
The aim of this work is to create a model for predicting the behavior of those leaving. Such a model has many applications, both for brick-and-mortar stores and online stores. Benefits include, for example, customer satisfaction and comfort. In more detail, I am describing the basic issue of predicting the next products. I am describing recommender systems as a whole, as well as their basic categorization and the basics of the individual models of the recommender systems. I am describing model, that I have created, for the dataset, that I chose to use and a procedure for working with the given model to predict the next purchase. I am also presentimg the procedure of our implementation in detail, as well as the results of testing.
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Deep Book Recommendation
Gráca, Martin ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This thesis deals with the field of Recommendation systems using Deep Neural Networks and their use in book recommendation. There are the main traditional recommender systems analysed and their representations are summarized, as well as systems with more advancec techniques based on machine learning.. The core of the thesis is the use of convolutional neural networks for natural language processing and the creation of a book recommendation system. Suggested system make recommendation based on user data, including user reviews and book data, including full texts.
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Návrh řešení studeného startu doporučovacího systému
MAŠTALÍŘ, Jakub
The main topic of the bacholor´s thesis is design and implementation of the recommender system´s module in the field of tourism and travelling. In the theoretical part the goal is mapping out an environment of the recommender system, their types and approaches. Furthermore there is described the problem of cold start and the theory of Bayes networks on the basis of which the data for the recommendation will be processed and presented. In the practical part we are programming and testing the recommender module. There is a description of the used technologies and individual functionalities of the recommender system aimed at the acommodation in České Budějovice are dismembered.
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Deep Book Recommendation
Gráca, Martin ; Kolář, Martin (referee) ; Hradiš, Michal (advisor)
This thesis deals with the field of recommendation systems using deep neural networks and their use in book recommendation. There are the main traditional recommender systems analysed and their representations are summarized, as well as systems with more advanced techniques based on machine learning. The core of the thesis is to use convolutional neural networks for natural language processing and create a hybrid book recommendation system. Suggested system includes matrix factorization and make recommendation based on user ratings and book metadata, including texts descriptions. I designed two models, one with bag-of-words technique and one with convolutional neural network. Both of them defeat baseline methods. On the created data set, that was created from the Goodreads, model with CNN beats model with BOW.
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Mobile Application for Presentation of Anime World Information
Odehnal, Jiří ; Rudnitckaia, Julia (referee) ; Hynek, Jiří (advisor)
This bachelor thesis deals with the design and development of a mobile application for Android platform as an extension of the existing Happo.cz web service. The aim of the work is to implement a simple and user-friendly user interface that provides basic information about animated films. The application should also support friendly relationships between users and encourage their mutual communication. Part of the thesis is also implementation of the server part and the content recommendation system.
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