Automated identification of tasks in email messages can be very useful to busy email users. What constitutes a task varies across individuals and must be learned for each user. However, training data for this purpose tends to be scarce. This paper addresses the lack of training data using domain-specific semantic features in document representation for reducing vocabulary mismatches and enhanci...

This contribution examines the macro quantitative features of 15 lowfrequency word classes. The relationship between word frequency classes and the sizes of the frequency classes obeys Altmann’s power law, and the sizes of lowfrequency word classes increase along with the increase of text length. The relationship between text length and the sizes of low-frequency word classes also obeys Altmann...

Most libraries use the machine-readable cataloguing (MARC) format to encode and exchange metadata about the items they make available to their patrons. Traditional library systems have not published this data on the Semantic Web. However, some agile open source library systems have begun closing this gap by publishing structured data that uses the schema.org vocabulary to describe the bibliogra...

This study aimed to investigate the effect of using vocabulary software on the vocabulary learning of Iranian EFL learners. Participants of the study were 54 intermediate-level students (23 males and 31 females) learning English as a foreign language in Mehr Institute in Izeh who were selected after taking the Nelson English Language Test as a proficiency test. They were randomly divided into t...

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...