Searched for: subject%3A%22recommender%255C%252Bsystems%22
(21 - 40 of 48)

Pages

List view
Grid view
document
van der Goes, Maurits (author)
The globalizing economy with its new goods and services, knowledge spread, and competition for talent is an increasing complexity for organizations, which requires organizations to adapt more quickly. Organizations are essential to society, as people are more productive in groups. For their continuity, it is important that organizations...
master thesis 2020
document
Knyazev, Norman (author)
Many widely used Recommender System algorithms estimate user tastes without accounting for their evolving nature. In recent years there has been a gradual increase in methods incorporating such temporal dynamics through sequential processing of user consumption histories. Some works have also included additional temporal features such as time...
master thesis 2020
document
Dingjan, Mitchell (author)
Recommender systems focus on automatically surfacing suitable items for users from digital collections that are too large for the user to oversee themselves. A considerable body of work exists on surfacing items that match what a user liked in the past; this way, the recommender system will exploit its knowledge of a user's comfort zone. However...
master thesis 2020
document
Salmi, Salim (author)
STUDY OBJECTIVE: Suicide crisis chat counsellors work in an environment which de- mands high emotional and cognitive awareness. A shared opinion among counsellors is that as the chat conversation turns more difficult it takes longer and more effort to come up with a response. Supportive technology might resolve this ”writer’s block” by giving...
master thesis 2019
document
Krishnaraj, Manoj (author)
Recommender systems (RS) often use a large amount of data for a marginal gain in performance. This thesis investigates the data minimization in Recommender Systems, which is not well studied in the literature. This thesis extends the data minimization principles advocated in GDPR and studies its effects on recommender systems. Minimizing data...
master thesis 2019
document
Los, Ben (author)
Because of the transfer from brick-and-mortar stores to the web, tourism companies have had an increasing need for good recommendation systems to help the users of their websites find what they want. When developing a recommendation system for tourism, we run into a couple of problems that we would not run into when developing it for e-commerce....
master thesis 2019
document
Feliciotti, Francesca Feliciotti (author)
During the last years, as virtual assistants such as Siri (Apple), Google Assistant, Amazon Alexa, spread into everyday situations, conversational recommender systems were proposed as an interactive recommendation process to connect with the user. However, there is little knowledge about the personalization of conversational recommender systems...
master thesis 2019
document
Hammudoğlu, Joren (author)
Recommender systems are essential for filtering immense amounts of available digital content. As these quantities keep increasing, the impact of recommendations does so as well. In this work, we address negative impacts current state-of-the-art recommenders have. For the algorithmic filtering of items that are recommended to users, collaborative...
master thesis 2019
document
Starmans, Ruben (author)
Web shops use recommender systems to help users find the products they find interesting in the large amount of available products online. An often used approach to do so is collaborative filtering. This method relies on historical user-item interactions and uses them to recommends products other users found interesting. Fashion is very reliant...
master thesis 2019
document
Walterbos, Alex (author)
This thesis focuses on the field of Job Recommendation. Particularly, we focus on using implicit preferences exhibited by the job seeker in interactions with a web platform to propose an improved ranking algorithm for a job recommendation platform called Magnet.me. We also study evaluation of relevance, and evaluation of recommendation sorting...
master thesis 2019
document
Dritsas, Athanasios (author)
In the last years, the popularity of video-on-demand services has been constantly increasing, especially for the young audiences who are more adept at using new technologies. Through those platforms, the viewers have access to a huge volume of movies at any moment that makes the viewing decision for most of them a very challenging task....
master thesis 2019
document
Jiang, Xuehan (author)
Information systems, such as information retrieval machines and recommendation systems, utilize various user information and history behaviors to provide personalized content to users. However, a debate on whether the personalization in information systems can trigger the online echo chamber effect has emerged. The online echo chamber effect...
master thesis 2018
document
Andreas Christian Pangaribuan, Andreas (author)
Users may show a behavioral pattern in consuming the items. For example, one might assume that a user is interested in comedy movies when this user watches comedy movies frequently. Recommender systems are designed to understand the preference of a user from his interactions with the items and suggest items that correspond to his preference....
master thesis 2018
document
Reza Aditya Permadi, Reza (author)
This thesis explores the effects of incorporating user consumption behavior and multiple types of user feedback to improve recommender systems for personalized music video television. An industrial use case is made possible by the availability of anonymized user interaction data on curation-based personalized music television system provided by...
master thesis 2018
document
Kumar, Jaya (author)
In recent years, personalized recommender systems have been facing criticism in research due to their ability to trap users in their circle of choices, called "filter-bubble", thereby limiting their exposure to novel content. In solving the issue of filter-bubble, past research has focused on providing explanations to users about how a...
master thesis 2018
document
Lu, Feng (author)
Current research on personality and diversity based Recommender Systems (RecSys) are mostly separated. In most diversity-based Recommender Systems, researchers usually endeavored to achieve an optimal balance between accuracy and diversity while they commonly set a same diversity level for all users. Different diversity needs for users with...
master thesis 2018
document
Ghanmode, Ishan (author)
In today’s digital world, users are often confronted with an abundance of information. Whether the user is looking to compare online prices for products, searching for new movies to watch or music to listen, the available information at hand exceeds the amount of information which the user wants to consider before making a choice. For this,...
master thesis 2018
document
Liang, Yu (author)
News recommendation is a field different from traditional recommendation fields. News articles are created and deleted continuously with a very short life cycle. Users' preference is also hard to model since they can easily be attracted by things happening around them. With all those challenges, traditional recommendation approaches, such as...
master thesis 2017
document
Jiao, Chongze (author)
Recent years, recommender systems are more and more important for solving information overload problem. They sort through massive data to provide users with personalized content and services. Most researchers focus on designing new algorithms to increase the performance of recommender systems. However, some open challenges stand: Why the...
master thesis 2017
document
van Kortenhof, B.L. (author)
Recommender systems help users explore a large data set by proposing items in that data set that the system expects to be of interest to that user. The use of context, information that describes in which situation a user interacts with the recommender system, has shown to increase the effectiveness of recommender systems in several domains. In...
master thesis 2017
Searched for: subject%3A%22recommender%255C%252Bsystems%22
(21 - 40 of 48)

Pages

List view
Grid view