In recent years, co-clustering has emerged as a powerful data mining tool that can analyze
dyadic data connecting two entities. However, almost all existing co-clustering techniques …

Cluster ensembles provide a framework for combining multiple base clusterings of a dataset
to generate a stable and robust consensus clustering. There are important variants of the …

Abstract Background The Naive Bayes (NB) classifier is a powerful supervised algorithm
widely used in Machine Learning (ML). However, its effectiveness relies on a strict …

This article addresses the problem of tracking moving objects using deformable models. A
Kalman-based algorithm is presented, inspired by a new class of constrained clustering …

Document clustering has been recognized as a central problem in text data management.
Such a problem becomes particularly challenging when document contents are …

Shilling attacks have been a significant vulnerability to collaborative filtering based
recommender systems recently. There are various studies focusing on detecting shilling …

Peer-to-peer data dissemination in a mobile ad-hoc environment is characterized by three
resource constraints, including energy, communication bandwidth, and storage. Most of the …

Family home visiting is a widely accepted strategy used with disadvantaged families to
mitigate the effects of poverty. However, gaps persist in knowledge of effective intervention …

针对情感分析需要大量人工标注语料的难点, 提出了一种面向无指导情感分析的层次性生成模型
. 该模型将朴素贝叶斯(NB) 模型和潜在狄利克雷分布(LDA) 相结合, 仅仅需要合适的情感词典 …

In this paper we proposed a hierarchical generative model based on Naïve Bayes and LDA
for unsupervised sentiment analysis at sentence level and document level of granularity …