Karur, Perambalur The k-nearest neighbor approach (k-NN) has been extensively used as a powerful non-parametric technique in many scientific and engineering applications. However, this approach incurs a large computational cost. Hence, this issue has become an active research field. In this work, a novel k-NN approach based on various-widths clustering, named kNNVWC, to efficiently find […]
Efficient Algorithms for Mining Top-K High Utility Itemsets
ieee projects 2016 Tanjore(Thanjavur), Pudukkottai High utility item sets (HUIs) mining is an emerging topic in data mining, which refers to discovering all item-sets having a utility meeting a user-specified minimum utility threshold min_util. However, setting min_util appropriately is a difficult problem for users. Generally speaking, finding an appropriate minimum utility threshold by trial and […]
Cross-Domain Sentiment Classification Using Sentiment Sensitive Embeddings
Bengaluru(Bangalore), Hyderabad 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 requiring any labeled data for the target domain. By adapting an existing sentiment classifier to previously unseen target domains, we can avoid the cost for manual data […]
Booster in High Dimensional Data Classification
Mumbai, Pune Classification problems in high dimensional data with a small number of observations are becoming more common especially in micro array data. During the last two decades, lots of efficient classification models and feature selection (FS) algorithms have been proposed for higher prediction ac-curacies. However, the result of an FS algorithm based on the […]
A Novel Recommendation Model Regularized with User Trust and Item Ratings
Chennai, Trichy We propose TrustSVD, a trust-based matrix factorization technique for recommendations. TrustSVD integrates multiple information sources into the recommendation model in order to reduce the data sparsity and cold start problems and their degradation of recommendation performance. An analysis of social trust data from four real-world data sets suggests that not only the explicit […]