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Big Data Research Group

University of Isfahan Big Data Research Group

Big data research group of Isfahan university

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گروه تحقیقاتی کلان‌داده دانشگاه اصفهان
Big data research group of Isfahan university
Big data research group of Isfahan university
Big data research group of Isfahan university

About Us

The Big Data Research Group, established at 2017, is located at the software engineering department of University of Isfahan, Isfahan, Iran.  There are currently more than 25 Ph.D. and 35 M.Sc. members in this group, working on mentioned area. An open-domain question answering system is now conducting in the big data research group.

Our Team

+6 Faculty members

We have currently 6 faculty members collaborating on big data lab's projects.

+20 Ph.D Members

There are 17 Ph.D candidates and 7 Ph.D students in our team and more will join us soon.

+25 M.Sc Members

We accept +10 M.Sc. students every year by the entrance exame.

+15 alumni Members

18 M.Sc. and Ph.D. students have graduated so far and more are going to graduate soon.

This group includes Big Data clusters, investing in Natural Language Proccessing, Data Mining, Complex Network Analysis, Machine Learning Applications, and Artificial Inteligent. Our aim is to develop and apply computationally efficient data analysis technologies for problems involving large amounts of data in different domains, with multidisciplinary collaborations between domain experts and computational researchers.

Big Data is a collection of massive and complex data sets and data volumes that include huge quantities of data, data management capabilities, social media analytics, and real-time data.

Machine learning is a field of inquiry devoted to understanding and building methods that ‘learn’, that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence.

A Complex Network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often occur in networks representing real systems.

Natural language Processing (NLP) is an area of computer science and artificial intelligence concerned with the interaction between computers and humans in natural language.

Dear colleagues, We are pleased to announce that the BigData Lab of the University of Isfahan has presented some large-scale datasets for Question Answering, Machine Reading Comprehension, and Answer Selection for the Persian language. We are very proud to share these datasets with our colleagues. These datasets are accessible from the links below:

In order to address the need for a high-quality QA dataset in the Persian language, we present PersianQuAD, the native QA dataset for the Persian language. We create PersianQuAD in four steps: 1) Wikipedia article selection, 2) question-answer collection, 3) three-candidates test set preparation, and 4) Data Quality Monitoring.

The Native Question Answering Dataset for the Persian Language

In order to address the need for a high-quality AS dataset in the Persian language, we present PASD; the first large-scale native AS dataset for the Persian language. To show the quality of PASD, we employed it to train state-of-the-art QA systems. We also present PerAnSel: a novel deep neural network-based system for Persian question answering.

A Novel Deep Neural Network-Based System for Persian QA

This paper introduces the Persian QA Dataset (ParSQuAD) based on the machine translation of the SQuAD 2.0 dataset. Many errors have been discovered within the process of translating the dataset; therefore, two versions of ParSQuAD have been generated depending on whether these errors have been corrected manually or automatically.

Persian QA Dataset based on Machine Translation of SQuAD 2.0

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