Abstract: Predicting gender by names is one of the most interesting problems in the domain of Information Retrieval and expert finding task. In this research paper, we propose a machine learning approach for gender prediction task. We propose a new feature, that is, combination of letters in names which gives 86.54% accuracy. Our data collection consists of 3000 Urdu language names written using English Alphabets. This technique can be used to extract names from email addresses and hence is also valid for emails. To the best of our knowledge, it is the first- ever attempt for predicting gender from Pakistani (Urdu) names written using English alphabets.

Daler Ali, Malik Muhammad Saad Missen, Nadeem Akhtar, Nadeem Salamat, Hina Asmat and Amnah Firdous, “Gender Prediction for Expert Finding Task” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070525

@article{Ali2016,
title = {Gender Prediction for Expert Finding Task},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070525},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070525},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Daler Ali and Malik Muhammad Saad Missen and Nadeem Akhtar and Nadeem Salamat and Hina Asmat and Amnah Firdous}
}