[PDF] Top 20 A New Sub-topic Clustering Method Based on Semi-supervised Learning
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A New Sub-topic Clustering Method Based on Semi-supervised Learning
... a new method of sub-topic clustering based on semi-supervised ...one topic, and labels the sentences which have high scores in the topic, then use the ... See full document
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A novel semi-supervised learning method based on fast search and density peaks
... a semi-supervised learning ...existing semi-supervised learning methods, we do not use unlabeled samples directly and, instead, look for safe and reliable unlabeled samples ... See full document
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An Efficient Iterative Framework for Semi-Supervised Clustering Based Batch Sequential Active Learning Approach
... Active learning has been studied extensively for supervised classification problems ...active learning for constraint-based clustering has been ...the semi-supervised ... See full document
7
Query focused Multi Document Summarization: Combining a Topic Model with Graph based Semi supervised Learning
... different clustering algorithms for summarization. Traditional clustering algorithms such as K-means, Agglomerative and Divisive clustering achieve comparative re- ...traditional clustering ... See full document
11
Semi Supervised Nonlinear Distance Metric Learning Via Random Forest and Relative Similarity Algorithm
... structures. Semi-supervised learning is a unification of supervised and unsupervised ...data. Semi- supervised learning models include self-training, mixture models, ... See full document
6
Detailed classification of swimming paths in the Morris Water Maze: multiple strategies within one trial
... a semi-automatic classification method is ...classification method, based on a semi-supervised class of machine learning algorithms, is able to automatically classify ... See full document
15
Morfessor FlatCat: An HMM Based Method for Unsupervised and Semi Supervised Learning of Morphology
... that semi-supervised FlatCat compares well against CatMAP in recall, for all morph patterns and for the test set as a whole, indicates that supervision indeed is effective in compensating for the ... See full document
9
SECURE ROUTING IN MANET USING ASYMMETRIC GRAPHS
... of semi-supervised K-means clustering algorithm based on active learning, to obtained the projection matrix under the action of the pairwise constraints and implemented LDA(Linear ... See full document
8
A New Homogeneity Inter Clusters Measure in Semi Supervised Clustering
... of semi-supervised clustering ...a new clustering method based on a new homogeneity measure between clusters considered as a ...proposed method is called ... See full document
9
A Review on health care examination records using data mining
... by Semi Supervised Learning. Semi-Supervised Learning is a situation in which in your training data some of the samples are not ...The semi-supervised estimators ... See full document
5
A new Semi-Supervised Intuitionistic Fuzzy C-means Clustering
... classical clustering algorithms to deal with the problem of uncertainty present in the real world unlabelled ...set based method helps to better handle the problem of uncertainty as compared to fuzzy ... See full document
12
A Graph Based Semi Supervised Learning for Question Semantic Labeling
... extract topic-focus from questions, (Ha- jicova et al., 1993) used rule-based approaches via dependency parser ...and learning methods to extract different salient features such as question type, ... See full document
9
Title: Improved Optimized Sentiment Classification On Dynamic Tweets
... a semi-supervised topic-adaptive sentiment classification (TASC) model, which starts with a classifier, built on common features and mixed labeled data from various ...including topic-related ... See full document
12
Partitioning The Documents Based On Semi-supervised Clustering Method.
... ourproposed Semi-supervised ...to new clusters in the semi-supervised ...The Semi-supervised approachacquires more precise estimation compared with the DMAFP ... See full document
6
AN EFFICIENT ITERATIVE FRAMEWORK FOR SEMI-SUPERVISED CLUSTERING BASED BATCH SEQUENTIAL ACTIVE LEARNING APPROACH
... Huang‟s method only considers the pairwise uncertainty of the first query, and fails to measure the benefit of the ensuing ...our method instead focuses on point-based uncertainty, which measures the ... See full document
6
Power Transformer Fault Diagnosis based on Deep Learning
... machine learning method, the deep learning neutral network (DLNN) is qualified enough to extract features from samples and transform such features and, it has a strong learning ability, thus ... See full document
7
Using Bilingual Comparable Corpora and Semi supervised Clustering for Topic Tracking
... the topic or ...1 topic from the TDT1 and 2 topics from the TDT2, each of which occurred in Japan, and added them in the ...Quake’ topic starts from ...denotes topic number de- fined by the ... See full document
8
Semi supervised Clustering for Short Text via Deep Representation Learning
... a semi- supervised method for short text clus- tering, where we represent texts as dis- tributed vectors with neural networks, and use a small amount of labeled data to specify our intention for ... See full document
9
Semi-supervised heterogeneous evolutionary co-clustering
... relative new topic. Earlier work was related to clustering of evolving ...the clustering on the evolving data should co-relate the current clusters with the previous clusters and suppress the ... See full document
43
An R*-Tree Based Semi-Dynamic Clustering Method for the Efficient Processing of Spatial Join in a Shared-Nothing Parallel Database System
... are called slave nodes, are isolated on a high-speed private network that is not directly visible to the outside world. A single computer connected to the outside world (called the master node) lets a user login to the ... See full document
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