Memory and language are important high-level cognitive functions of humans, the study conceptual representation human brain is a key approach to reveal principles cognition. However, this research often constrained by availability stimulus materials. The on concept needs be based standardized large-scale database semantic features. Although Western scholars have established variety English feat...

the persian morpheme ra has attracted the attention of many linguists including karimi (1989), dabir-moghaddam (1990) and ghomeshi (1996) among others. karimi takes ra as the accusative case marker, the presence of which on subjects and objects of prepositions render the sentence ungrammatical. according to ghomeshi (1996), it marks dps functioning as vp-level topics. dabir-moghaddam (1990) ana...

Background: Knowing the development pattern of children’s language is applicable in developmental psychology. Network models of language are helpful for the identification of these patterns.  Objectives: We examined the small-world properties of featured semantic networks of developing children. Materials & Methods: In this longitudinal study, the featured semantic networks of children aged 1...

Unsupervised domain adaptation (UDA) deals with the task that labeled training and unlabeled test data collected from source and target domains, respectively. In this paper, we particularly address the practical and challenging scenario of imbalanced cross-domain data. That is, we do not assume the label numbers across domains to be the same, and we also allow the data in each domain to be coll...

Incorporating multiple types of relational information from heterogeneous networks has been proved effective in data mining. Although Wikipedia is one of the most famous heterogeneous network, previous works of semantic analysis on Wikipedia are mostly limited on single type of relations. In this paper, we aim at incorporating multiple types of relations to measure the semantic relatedness betw...

In this paper, we propose a semantic naïve Bayes classifier (SNBC) to improve the conventional naïve Bayes classifier (NBC) by incorporating “document-level” semantic information for document classification (DC). To capture the semantic information from each document, we develop semantic feature extraction and modeling algorithms. For semantic feature extraction, we first apply a log-Bilinear d...