Search Results for author:
Found 21 papers, 4 papers with code
Pars-ABSA: a Manually Annotated Aspect-based Sentiment Analysis Benchmark on Farsi Product Reviews
Due to the increased availability of online reviews, sentiment analysis witnessed a thriving interest from researchers.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
Emulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules
To tackle the challenge of dealing with incorrect paths or rules generated by the logical model, we propose a semi-supervised method to convert rules into sentences.
Noor-Ghateh: A Benchmark Dataset for Evaluating Arabic Word Segmenters in Hadith Domain
In terms of the volume and variety of words, this dataset is superior to other existing data sets, and as far as we know, there are no Arabic Hadith Domain texts.
Farspredict: A benchmark dataset for link prediction
To evaluate Farspredict, we implemented the popular models of KGE on it and compared the results with Freebase.
Evaluating Persian Tokenizers
Natural Language Processing in Persian is challenging due to Persian's exceptional cases, such as half-spaces.
ParsFEVER: a Dataset for Farsi Fact Extraction and Verification
Training and evaluation of automatic fact extraction and verification techniques require large amounts of annotated data which might not be available for low-resource languages.
KGRefiner: Knowledge Graph Refinement for Improving Accuracy of Translational Link Prediction Methods
The Link Prediction is the task of predicting missing relations between entities of the knowledge graph.
Ranked #2 on
Link Prediction
on FB15k-237
(training time (s) metric)
A Sample-Based Training Method for Distantly Supervised Relation Extraction with Pre-Trained Transformers
In the proposed method, we limit the number of sentences in a batch by randomly sampling sentences from the bags in the batch.
Interval Probabilistic Fuzzy WordNet
Utilizing our algorithm and the open-American-online-corpus (OANC) and UKB word-sense-disambiguation, we constructed and published the IPF synsets of WordNet for English language.
An Unsupervised Language-Independent Entity Disambiguation Method and its Evaluation on the English and Persian Languages
Entity Linking is one of the essential tasks of information extraction and natural language understanding.
IUST at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text using Deep Neural Networks and Linear Baselines
Our group, with the name of IUST(username: TAHA), participated at the SemEval-2020 shared task 9 on Sentiment Analysis for Code-Mixed Social Media Text, and we have attempted to develop a system to predict the sentiment of a given code-mixed tweet.
Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm Detection
Sarcasm is a type of figurative language broadly adopted in social media and daily conversations.
Ranked #1 on
Sarcasm Detection
on FigLang 2020 Reddit Dataset
(using extra training data)
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
PERLEX: A Bilingual Persian-English Gold Dataset for Relation Extraction
The main motivations of this research stem from a lack of a dataset for relation extraction in the Persian language as well as the necessity of extracting knowledge from the growing big-data in the Persian language for different applications.
FarsBase-KBP: A Knowledge Base Population System for the Persian Knowledge Graph
While most of the knowledge bases already support the English language, there is only one knowledge base for the Persian language, known as FarsBase, which is automatically created via semi-structured web information.
ParsEL 1.0: Unsupervised Entity Linking in Persian Social Media Texts
Entity linking is the task of linking the entity mentions in the text to their corresponding entities in a knowledge base.
Pars-ABSA: an Aspect-based Sentiment Analysis dataset for Persian
Due to the increased availability of online reviews, sentiment analysis had been witnessed a booming interest from the researchers.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
A new selection strategy for selective cluster ensemble based on Diversity and Independency
In recent years, Diversity and Quality, which are two metrics in evaluation procedure, have been used for selecting basic clustering results in the cluster ensemble selection.
Evaluating the effect of topic consideration in identifying communities of rating-based social networks
Finding meaningful communities in social network has attracted the attentions of many researchers.
Multi-View Learning for Web Spam Detection
In order to design a multi-view classification system, we used state-of-the-art spam classification methods with distinct feature sets (views) as the base classifiers.
A Framework for Spelling Correction in Persian Language Using Noisy Channel Model
Our evaluation results show that Noisy Channel Model using our corpus and training set in this framework works more accurately and improves efficiently in comparison with other methods.
