by admin | Jun 24, 2016 | 2016 ieee projects
Incremental Semi-Supervised Clustering Ensemble for High Dimensional Data Clustering Traditional cluster ensemble approaches have three limitations: (1) They do not make use of prior knowledge of the datasets given by experts. (2) Most of the conventional cluster...
by admin | Jun 24, 2016 | 2016 ieee projects
High utility itemsets (HUIs) mining is an emerging topic in data mining, which refers to discovering all itemsets having a utility meeting a user-specified minimum utility threshold min_util. However, setting min_util appropriately is a difficult problem for users....
by admin | Jun 24, 2016 | 2016 ieee projects
Collaborative Filtering (CF) is one of the most successful recommendation approaches to cope with information overload in the real world. However, typical CF methods equally treat every user and item, and cannot distinguish the variation of user’s interests...
by admin | Jun 24, 2016 | 2016 ieee projects
Querying uncertain data has become a prominent application due to the proliferation of user-generated content from social media and of data streams from sensors. When data ambiguity cannot be reduced algorithmically, crowdsourcing proves a viable approach, which...
by admin | Jun 24, 2016 | 2016 ieee projects
Cross-Domain Sentiment Classification Using Sentiment Sensitive Embeddings Unsupervised Cross-domain Sentiment Classification is the task of adapting a sentiment classifier trained on a particular domain (source domain), to a different domain (target domain), without...