Search Results for author: Mohammad-Ali Balafar

Found 8 papers, 0 papers with code

Text-Based Automatic Personality Prediction Using KGrAt-Net; A Knowledge Graph Attention Network Classifier

no code implementations27 May 2022 Majid Ramezani, Mohammad-Reza Feizi-Derakhshi, Mohammad-Ali Balafar

For the first time, it applies the knowledge graph attention network to perform Automatic Personality Prediction (APP), according to the Big Five personality traits.

Graph Attention Knowledge Graph Embedding +1

Knowledge Graph-Enabled Text-Based Automatic Personality Prediction

no code implementations17 Mar 2022 Majid Ramezani, Mohammad-Reza Feizi-Derakhshi, Mohammad-Ali Balafar

This paper presents a novel knowledge graph-enabled approach to text-based APP that relies on the Big Five personality traits.

Graph-Based Recommendation System Enhanced with Community Detection

no code implementations10 Jan 2022 Zeinab Shokrzadeh, Mohammad-Reza Feizi-Derakhshi, Mohammad-Ali Balafar, Jamshid Bagherzadeh-Mohasefi

On the other hand, due to the change of users' interests over time this article has considered the time of tag assignments in co-occurrence tags for determining similarity of tags.

Community Detection Recommendation Systems +3

TopicBERT: A Transformer transfer learning based memory-graph approach for multimodal streaming social media topic detection

no code implementations16 Aug 2020 Meysam Asgari-Chenaghlu, Mohammad-Reza Feizi-Derakhshi, Leili farzinvash, Mohammad-Ali Balafar, Cina Motamed

These properties of social networks which are known as 5'Vs of big data has led to many unique and enlightenment algorithms and techniques applied to large social networking datasets and data streams.

Community Detection Graph Mining +4

A Model to Measure the Spread Power of Rumors

no code implementations18 Feb 2020 Zoleikha Jahanbakhsh-Nagadeh, Mohammad-Reza Feizi-Derakhshi, Majid Ramezani, Taymaz Akan, Meysam Asgari-Chenaghlu, Narjes Nikzad-Khasmakhi, Ali-Reza Feizi-Derakhshi, Mehrdad Ranjbar-Khadivi, Elnaz Zafarani-Moattar, Mohammad-Ali Balafar

To address this research gap, the present study seeks a model to calculate the Spread Power of Rumor (SPR) as the function of content-based features in two categories: False Rumor (FR) and True Rumor (TR).

Rumour Detection

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