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...

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...

ontology is the main infrastructure of the semantic web which provides facilities for integration, searching and sharing of information on the web. development of ontologies as the basis of semantic web and their heterogeneities have led to the existence of ontology matching. by emerging large-scale ontologies in real domain, the ontology matching systems faced with some problem like memory con...

Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use...

Image clustering is an important and open challenging task in computer vision. Although many methods have been proposed to solve the image task, they only explore images uncover clusters according features, thus being unable distinguish visually similar but semantically different images. In this paper, we propose investigate of with help visual-language pre-training model. Different from zero-s...

  One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...