The market of mobile phone gets expanded with gradual increase in smartphone demands at an aggressive phase and this booming over smartphone industries have provocative an essential for realizing the complete features of the phone models and the brand. However, the electronic commerce has played a major role in improving the mobile phone sales and even prompted the pattern of consumer buying. The information at anywhere and anytime is the style mantra in usage with improved rate due to development of smartphone. Hence, there are numerous products manufactured by several dissimilar brands but providing relevant features to customer is hour of need. In addition, confessing of intricate relationship among entities has become an important to business decision, prediction and optimization. This relationship not only involves explicit based on co-occurrence and even considered implicit relation based on non-co-occurrences. In most of the association rule get focused on explicit relation that are considered as a rule mining based methods but the focus on relationship of implicit is addressed very low due to less frequency itemsets. Therefore, this paper has addressed the implicit relationship among items that occur rarely or doesn’t occur when each itemsets co-occurs with other identical items with high possibility. This paper has initiated with two phases namely explicit and hidden item dependencies which get integrated using algorithm of Integrated Implicitly Rule (IIR) that assist in seizure implicit relationship. The input survey of Google form has been taken from students and staffs of Anna University is provided with smartphone feature expectation based on recent trends. This analysis provide the data about requirement from customer with least frequency but high probability that assist the retailer and manufacture to focus on the particular features to cover all aspects of featured smartphone.Moreover, an implementation of IRR algorithm is to generate recommendations and illustrate the identified implicit rules which can increases recommendation reliability.