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Detecting Emerging Trends from Scientific Corpora
Emerging trend detection is a new challenge and an attractive topic in text mining. Our research goal was to construct a model to detect emerging trends in a set of scientific articles; the resultingExpand
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Vietnamese treebank construction and entropy-based error detection
TLDR
We present our method for automatically finding errors and inconsistencies in treebank corpora and its application to the construction of the VTB. Expand
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Blended learning model on hands-on approach for in-service secondary school teachers: Combination of E-learning and face-to-face discussion
TLDR
The purpose of this study was to examine the effectiveness of a blended learning model on hands-on approach for in-service secondary school teachers using a quasi-experimental design. Expand
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Advances in Knowledge Discovery and Data Mining
TLDR
This paper presents a novel approach on Chinese micro-blog emotion cause detection based on the ECOCC model, focusing on mining factors for eliciting some kinds of emotions. Expand
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Cluster-based Algorithms for Filling Missing Values
We first survey existing methods to deal with missing values and report the results of an experimental comparative evaluation in terms of their processing cost and quality of imputing missing values.Expand
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Detecting disease genes based on semi-supervised learning and protein-protein interaction networks
TLDR
This work aims to find an effective method to exploit the disease gene neighbourhood and the integration of several useful omics data sources, which potentially enhance disease gene predictions by exploiting semi-supervised learning. Expand
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A Fuzzy Target Based Model for Decision Making Under Uncertainty
TLDR
We extend the target-based model for decision making under uncertainty using fuzzy targets, making use of Yager's procedure of converting possibility distributions into probability ones via a simple normalization. Expand
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An evolutionary K-means algorithm for clustering time series data
TLDR
We propose an evolutionary K-means clustering algorithm to attack this problem. Expand
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System pharmacology: Application of network theory in predicting potential adverse drug reaction based on gene expression data
TLDR
In drug development process, adverse drug reaction (ADR) is one of the biggest challenges to evaluate the drug safety for passing to the market. Expand
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Mixture of Language Models Utilization in Score-Based Sentiment Classification on Clinical Narratives
TLDR
The paper shows that a sentiment score of a sentence simultaneously depends on scores of its terms including words, phrases, sequences of non-adjacent words, thus we propose to use a linear combination which can incorporate the scores of the terms extracted by various language models. Expand
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