Tweet Rating Dataset

This dataset contains tweets of users about the items of four popular and diverse web applications: IMDb (movie), YouTube (video clip), Pandora (music), and Goodreads (book). This dataset contains ~500K tweets from ~20K users about ~230K items (movie, music, etc.). This dataset is freely available for research purposes. Tweet Rating Dataset can be downloaded from here. Citation:

  1. Adaptive User Engagement Evaluation via Multi-task Learning Hamed Zamani, Pooya Moradi, and Azadeh Shakery In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015 (SIGIR ’15)

PAL: Preference/Ranking Aggregation Library

This Ruby library contains a few simple rank aggregation methods that we used in ACM RecSysChallenge 2014. The package is open-sourced and can be found here. Citation:

  1. Regression and Learning to Rank Aggregation for User Engagement Evaluation Hamed Zamani, Azadeh Shakery, and Pooya Moradi In Proceedings of the 2014 Recommender Systems Challenge, 2014 (RecSysChallenge ’14)

Wikipedia English-Persian Parallel Corpus

This parallel corpus is automatically extracted from English and Persian Wikipedia articles. We extensively evaluate our created parallel corpus to show its high quality compared to the existing English-Persian parallel corpora. This dataset is freely available for research purposes. To download the parallel corpus, please visit here. Citation:

  1. Sentence Alignment Using Local and Global Information Hamed Zamani, Heshaam Faili, and Azadeh Shakery Computer Speech & Language, 2016 (CSL)