"clustering Words" Clustering Words Clustering Words
نویسندگان
چکیده
منابع مشابه
The Impact of Semantic Clustering on Iranian EFL Advanced Learners’ Vocabulary Retention
This study investigated the impact of semantic clustering on Iranian EFL learners’ vocabulary retention at advanced level. Participants were female learners randomly assigned to two groups of 15. Four instruments (TOEFL test; vocabulary pretest; immediate posttest, and delayed recall posttest) were used. The experimental group underwent semantic clustering vocabulary presentation in which the l...
متن کاملWord clustering effect on vocabulary learning of EFL learners: A case of semantic versus phonological clustering
The aim of this study is to determine the effect of word clustering method on vocabulary learning of Iranian EFL learners through a case of semantic versus phonological clustering. To this effect, 80 homogeneous students from four intermediate classes at an English institute in Torbat e Heydariyeh participated in this research. They were assigned to four groups according to semantic versus phon...
متن کاملUnderstanding bag-of-words model: a statistical framework
The bag-of-words model is one of the most popular representation methods for object categorization. The key idea is to quantize each extracted key point into one of visual words, and then represent each image by a histogram of the visual words. For this purpose, a clustering algorithm (e.g., K-means), is generally used for generating the visual words. Although a number of studies have shown enc...
متن کاملComputational Intelligence Methods for Clustering of Sense Tagged Nepali Documents
This paper presents a method using hybridization of self organizing map (SOM ), particle swarm optimization(PSO) and k-means clustering algorithm for document clustering. Document representation is an important step for clustering purposes. The common way of represent a text is bag of words approach. This approach is simple but has two drawbacks viz. synonymy and polysemy which arise because of...
متن کاملA Text Clustering System based on k-means Type Subspace Clustering and Ontology
This paper presents a text clustering system developed based on a k-means type subspace clustering algorithm to cluster large, high dimensional and sparse text data. In this algorithm, a new step is added in the k-means clustering process to automatically calculate the weights of keywords in each cluster so that the important words of a cluster can be identified by the weight values. For unders...
متن کامل