Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
Optimizing CELF Algorithm for Influence Maximization Problem in Social Networks

M. Taherinia; M. Esmaeili; B. Minaei Bidgoli

Volume 10, Issue 1 , January 2022, , Pages 25-41

https://doi.org/10.22044/jadm.2021.10964.2254

Abstract
  The Influence Maximization Problem in social networks aims to find a minimal set of individuals to produce the highest influence on other individuals in the network. In the last two decades, a lot of algorithms have been proposed to solve the time efficiency and effectiveness challenges of this NP-Hard ...  Read More

ParsNER-Social: A Corpus for Named Entity Recognition in Persian Social Media Texts

M. Asgari-Bidhendi; B. Janfada; O. R. Roshani Talab; B. Minaei-Bidgoli

Volume 9, Issue 2 , April 2021, , Pages 181-192

https://doi.org/10.22044/jadm.2020.9949.2143

Abstract
  Named Entity Recognition (NER) is one of the essential prerequisites for many natural language processing tasks. All public corpora for Persian named entity recognition, such as ParsNERCorp and ArmanPersoNERCorpus, are based on the Bijankhan corpus, which is originated from the Hamshahri newspaper in ...  Read More

H.3.5. Knowledge Representation Formalisms and Methods
Context-aware Modeling for Spatio-temporal Data Transmitted from a Wireless Body Sensor Network

N. Khozouie; F. Fotouhi Ghazvini; B. Minaei

Volume 7, Issue 4 , November 2019, , Pages 575-588

https://doi.org/10.22044/jadm.2018.6005.1707

Abstract
  Context-aware systems must be interoperable and work across different platforms at any time and in any place. Context data collected from wireless body area networks (WBAN) may be heterogeneous and imperfect, which makes their design and implementation difficult. In this research, we introduce a model ...  Read More

H.3.8. Natural Language Processing
An improved joint model: POS tagging and dependency parsing

A. Pakzad; B. Minaei Bidgoli

Volume 4, Issue 1 , March 2016, , Pages 1-8

https://doi.org/10.5829/idosi.JAIDM.2016.04.01.01

Abstract
  Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do ...  Read More