Tag recommendation is one of the challenging problems in data mining of text. Tagging lets users explore related content, and is very useful on software information sites like Stack Overflow, Stack Exchange sites, Quora, internet forums, etc. In this paper, I tried to develop another software information site named ASK-ME, with an improved automatic tag recommender based on historical tag assignments to software objects using combination of Bayesian Inference and Frequentist Inference collectively known as ENTAGREC. It achieves accuracy expressed in terms of recall scores of 0.805 for 5 fold cross validation and 0.868 for 10 fold cross validation, using Stack Overflow dataset.