most citedPredicting Subjective Features of Questions of QA Websites using BERT

18 citations · 48 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2020

Tag Recommendation for Online Q&A Communities based on BERT Pre-Training Technique

Navid Khezrian, Jafar Habibi, Issa Annamoradnejad

Online Q&A and open source communities use tags and keywords to index, categorize, and search for specific content. The most obvious advantage of tag recommendation is the correct…

cs.LG2020

Using Experts' Opinions in Machine Learning Tasks

Jafar Habibi, Amir Fazelinia, Issa Annamoradnejad

In machine learning tasks, especially in the tasks of prediction, scientists tend to rely solely on available historical data and disregard unproven insights, such as experts' opin…

cs.CL2020★ 17 cited

ColBERT: Using BERT Sentence Embedding in Parallel Neural Networks for Computational Humor

Issa Annamoradnejad, Gohar Zoghi

Automation of humor detection and rating has interesting use cases in modern technologies, such as humanoid robots, chatbots, and virtual assistants. In this paper, we propose a no…

cs.CL2020★ 18 cited

Predicting Subjective Features of Questions of QA Websites using BERT

Issa Annamoradnejad, Mohammadamin Fazli, Jafar Habibi

Community Question-Answering websites, such as StackOverflow and Quora, expect users to follow specific guidelines in order to maintain content quality. These systems mainly rely o…

cs.SI2019★ 13 cited

A Comprehensive Analysis of Twitter Trending Topics

Issa Annamoradnejad, Jafar Habibi

In Twitter, a name, phrase, or topic that is mentioned at a greater rate than others is called a "trending topic" or simply "trend". Twitter trends list has a powerful ability to p…