Clauses and the semantic representation of words.

Named Entity Recognition in Persian Text using Deep Learning

Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...

Word Type Effects on L2 Word Retrieval and Learning: Homonym versus Synonym Vocabulary Instruction

The purpose of this study was twofold: (a) to assess the retention of two word types (synonyms and homonyms) in the short term memory, and (b) to investigate the effect of these word types on word learning by asking learners to learn their Persian meanings. A total of 73 Iranian language learners studying English translation participated in the study. For the first purpose, 36 freshmen from an ...

برچسب‌زنی خودکار نقش‌های معنایی در جملات فارسی به کمک درخت‌های وابستگی

Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...

The Effect of Semantic Transfer on Iranian EFL Learners’ Lexical Representation and Processing

A Joint Semantic Vector Representation Model for Text Clustering and Classification

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...

Complementiser Phrase: The Case of English Wh-Embedded Clauses

English main-clause wh-questions form complementiser phrases with wh-words preposed to spec-C position. This is because English wh-words, as verb-complements originally, are strong enough to trigger wh-movement and auxiliary inversion. Persian EFL learners encounter an over-differentiation problem regarding the acquisition of auxiliary inversion rule in English standard questions. Once they hav...