Multiple-vector user profiles in support of knowledge sharing

Exploring synergies between content-based filtering and Spreading Activation techniques in knowledge-based recommender systems

“…These descriptions permit a recommender system to learn new knowledge about the user's interests, which is not possible with many of the existing user modeling techniques: Some existing works define too simple user models, containing only flat lists of key words (e.g. attributes) or ratings referred to each item defined in the user's profile [11,24,39]. These proposals provide little knowledge about the user's preferences, and therefore hamper the application of advanced reasoning processes.…”

Distributed recommender for peer-to-peer knowledge sharing

“…For knowledge sharing, the agent based technologies and distributed knowledge management (KM) methods were widely used [10,17,25,27]. In addition, game theory [3], cognitive theory [6], and some social science method [20] were also employed to model knowledge sharing interactions among people.…”

Strategic interaction support for knowledge sharing in virtual communities

“…A weight of 0 indicates that a word from the vocabulary is not present. There exists a large number of weighting schemes to assign weights to dimensions, the most popular including TF-IDF, BM25 and Log-entropy [6].…”