4/29/2023 0 Comments Creating noddes docear![]() Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. Such systems could create additional value for millions of mind-mapping users.Ībstract: Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Our findings let us to conclude that user modeling based on mind maps is a promising research field, and that developers of mind-mapping applications should integrate recommender systems into their applications. In addition, we show that user modeling based on mind maps performs about as well as user modeling based on other items, namely the research articles users downloaded or cited. When all variables are combined in a favorable way, this novel approach achieves click-through rates of 7.20%, which is nearly twice as effective as the best baseline. We find, among others, that the number of analyzed nodes, modification time, visibility of nodes, relations between nodes, and number of children and siblings of a node affect the effectiveness of user modeling. As part of our research, we identify several variables relating to mind-map-based user modeling, and evaluate the variables' impact on user-modeling effectiveness with an offline evaluation, a user study, and an online evaluation based on 430,893 recommendations displayed to 4,700 users. The recommender system builds user models based on the mind maps, and recommends research papers based on the user models. To achieve this objective, we integrate a recommender system in our mind-mapping and reference-management software Docear. The objective of this doctoral thesis is to develop an effective user-modeling approach based on mind maps. Hence, millions of mind-mapping users could benefit from user-modeling applications such as recommender systems. We consider this a serious shortcoming since we assume user modeling based on mind maps to be equally effective as user modeling based on other items. Abstract: While user-modeling and recommender systems successfully utilize items like emails, news, and movies, they widely neglect mind-maps as a source for user modeling.
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