The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of features. Some techniques, such as Latent Semantic Analysis (LSA) or Latent Dirichlet Allocation (LDA), have been designed to summarize documents in a lower dimension with the least semantic information loss. Some sema...

Abstract We analyse how ambitiously the underlying targets for Sustainable Development Goals (SDGs) of United Nations Agenda 2030 are set in terms their semantic formulation and discuss implications this policy making. Our analysis is based on classifying ambitiousness into three types: semantic, relative absolute ambitiousness; paper, we mainly . establish an evaluation framework that shows cl...

Speech is one of the most opulent and instant methods to express emotional characteristics of human beings, which conveys the cognitive and semantic concepts among humans. In this study, a statistical-based method for emotional recognition of speech signals is proposed, and a learning approach is introduced, which is based on the statistical model to classify internal feelings of the utterance....

this paper examines the semantic contribution of -?r and -andeh suffixes in persian based on lieber’s (2004) lexical semantic representation. this framework using six semantic features ([material], [dynamic], [location], [ieps] , [b] and [ci] and a principle called coordination principle studies the semantic contribution of lexical items including affixes and their functions in compounding, der...

Categories are not invariant. This paper attempts to explore the dynamic nature of semantic category, in particular, that of fashion language, based on the cognitive theory of Dawkins’ memetics, a new theory of cultural evolution. Semantic attributes of linguistic memes decrease or proliferate in replication and spreading, which involves a dynamic development of semantic category. More specific...