The　development　of　information　technologies　raises　the　problem　of　information　overload.　Recommender　systems　aim　to　choose　the　best　application　or　content　from　numerous　applications　or　contents.　And　contextual　information　has　been　taken　into　account　to　improve　the　recommendation　accuracy.　Inspired　by　a　cognitive　architecture　named　ACT-R,　this　paper　combines　frequency　and　recency　into　contextual　information　to　provide　context-based　recommendations　for　mobile　applications.　The　experimental　results　show　the　ACT-R　inspired　method　is　effective　in　context-based　recommendations.