The main aim of the thesis is to determine, how the order of functions in the source code will affect the program comprehension […]
PeWe.Data OA-2017
Recommendation Taking into Account the Time Aspects of Users and Items
The role of reference systems is based on previous user activity that predicts interest in new item s (e.g., Ecommerce Products). Most systems, […]
Interpretabilty of Machine Learning Models created by Clustering Algorithms
Interpretability is a key characteristics of machine learning model, if our goal is to persuade experts from chosen domain, for which we propose […]
Aspect Based Sentiment Analysis
Text data produced on social networks like Facebook continuously increase. Reading and evaluating these posts manualy is very time consuming so our research […]
Improving Robustness Against Websites’ Changes During Web Data Extraction
General approach to dealing with changes to the websites’ structure during web extraction is to optimize the XPath expressions before executing the wrapper. […]
Prediction of users’ personality traits based on task solving on the Web
Nowadays, people use web applications and systems to a greater extent than in the past. They want to gain information, realize different services […]
Predicting User Retention in online enviroment
The recent growth of market and technology advancement led to the increse of amount of competitors providing online services to its users. In […]
Scalable Personalized Recommendation
Do you know that feeling when you dont know which movie to watch? The more movies are in offer the harder it is […]
Personalized Recommendation Taking into Account Visual Impacts
Recommender system is important part of the web nowadays. Amount of information on the web is just unsearchable and to find useful informations […]
Personalized recommendation considering visual influences
Recommender systems are typical solution to information overload of users. Recommendations created by these systems can contain most popular items, but it was […]