I have crawled MTurk website. and I have 260 Hits as a dataset and from this dataset particular number of users has selected Hits and assigned ratings to each selected Hits. now I want to give recommendation to these users on basis of their selection. How it is possible ? Can anyone recommend me any recommendation algorithm ?
It sounds that You should go for the one of the Collaborative Filtering (CF) algorithm as users have explicit feedback in a form of ratings. First, I would suggest implementing a simple item/user-based k-Nearest Neighbours algorithm. If the results do not satisfy You and maybe Your data is very sparse - probably matrix factorization techniques should do the trick. A good recently survey which I read was [1] - it presents the different methods on different data settings.
If You fill fill comfortable with this and You realize that what You need is actually ranked list of Top-N predictions than ratings, I would suggest reading about e.g. Bayesian Personalized Ranking[2].
And the best part is - those algorithms are really well known and most of them are available for almost every programming language, e.g. python -> https://github.com/Mendeley/mrec/
[1] J. Lee, M. Sun, and G. Lebanon, “A Comparative Study of Collaborative Filtering Algorithms,” ArXiv, pp. 1–27, 2012.
[2] S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-thieme, “BPR : Bayesian Personalized Ranking from Implicit Feedback,” in Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, 2009, vol. cs.LG, pp. 452–461.