In this paper, the authors analyze the customer reviews on restaurant domain using sentiment analysis and text mining techniques. The most integral part of their work is to assign Sentiment scores to the aspects with respect to the words used. The authors have devised Sentiscore algorithm to perform this function. The dataset they have at their disposal is a set of review documents obtained from an authenticated repository. They perform an aspect level sentiment extraction thereby, attempting to mine and understand the user's feedback data. The aspects that they have taken into account are food, cost, ambience and service. A priority-based algorithm forms the rule base for the classifier to predict the polarity of the reviews.