Learning of domain dependent knowledge in semantic networks

Presenting a method for extracting structured domain-dependent information from Farsi Web pages

Extracting structured information about entities from web texts is an important task in web mining, natural language processing, and information extraction. Information extraction is useful in many applications including search engines, question-answering systems, recommender systems, machine translation, etc. An information extraction system aims to identify the entities from the text and extr...

Query Architecture Expansion in Web Using Fuzzy Multi Domain Ontology

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

The Effects of Guided and Unguided Semantic Mapping on Iranian EFL Learners’ Vocabulary and Grammar Knowledge

Investigating the Effect of Morphology Instruction through Semantic Map-ping on Vocabulary Learning of Iranian Intermediate EFL Learners

  The aim of this study was to investigate the effect of morphology instruction through semantic mapping on vocabulary learning of Iranian intermediate EFL learners. To do so, 50 out of 70 students were se-lected from one English language institute by administrating a PET test. Then, they were assigned into two groups randomly as experimental and control groups. A pretest (teacher made) was adm...

Image Classification via Sparse Representation and Subspace Alignment

Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...