1. A method for ranking one or more products in online shopping, the method comprising the steps of: a) receiving a keyword search query for the one or more products, the one or more products being associated with a product category; b) identifying one or more attributes, based on receiving the keyword search query, related to the product category, the one or more attributes comprising at least one of a brand name, a store name, a style, and price; c) selecting one of the one or more identified attributes as a base attribute, wherein the base attribute is selected based on the product category; d) identifying one or more features corresponding to the base attribute, the one or more features comprising query independent features and query dependent features; e) computing a normalized score of each of an attribute instance of the base attribute for each product in the product category, the normalized score being computed based on the value associated with each of the one or more features associated with the base attribute, wherein the value of the one or more features is determined based on a query dependent and a query independent analysis of the one or more features, the normalized score being computed using one or more mathematical functions; f) computing a normalized score of each of an attribute instance of the one or more attributes other than the base attribute for each product in the product category, the normalized score being computed based at least in part on the normalized score of the corresponding base attribute instance of each product, the normalized score being computed using one or more mathematical functions and an attribute affinity matrix, wherein the attribute affinity matrix comprises one or more values, for the attribute instance of the one or more attributes other than the base attribute, calculated based on normalized scores of the attribute instances of the base attribute; g) assigning weights to each of the one or more attributes based on the relative importance of each of the one or more attributes for the product category and the keyword search query; h) generating a product rank for each of the one or more products in the product category based on the assigned weights of the one or more attributes and the scores of each attribute instance using a predefined relevancy-ranking algorithm; and i) displaying a rank ordered list of the one or more products, wherein the steps of the method are performed by a microprocessor.
1. A method for ranking one or more products in online shopping, the method comprising the steps of: a) receiving a keyword search query for the one or more products, the one or more products being associated with a product category; b) identifying one or more attributes, based on receiving the keyword search query, related to the product category, the one or more attributes comprising at least one of a brand name, a store name, a style, and price; c) selecting one of the one or more identified attributes as a base attribute, wherein the base attribute is selected based on the product category; d) identifying one or more features corresponding to the base attribute, the one or more features comprising query independent features and query dependent features; e) computing a normalized score of each of an attribute instance of the base attribute for each product in the product category, the normalized score being computed based on the value associated with each of the one or more features associated with the base attribute, wherein the value of the one or more features is determined based on a query dependent and a query independent analysis of the one or more features, the normalized score being computed using one or more mathematical functions; f) computing a normalized score of each of an attribute instance of the one or more attributes other than the base attribute for each product in the product category, the normalized score being computed based at least in part on the normalized score of the corresponding base attribute instance of each product, the normalized score being computed using one or more mathematical functions and an attribute affinity matrix, wherein the attribute affinity matrix comprises one or more values, for the attribute instance of the one or more attributes other than the base attribute, calculated based on normalized scores of the attribute instances of the base attribute; g) assigning weights to each of the one or more attributes based on the relative importance of each of the one or more attributes for the product category and the keyword search query; h) generating a product rank for each of the one or more products in the product category based on the assigned weights of the one or more attributes and the scores of each attribute instance using a predefined relevancy-ranking algorithm; and i) displaying a rank ordered list of the one or more products, wherein the steps of the method are performed by a microprocessor. 9. The method according to claim 1 , wherein the one or more features are associated with market demand-supply characteristics for the product, wherein the one or more features associated with the market demand-supply characteristics for the product are at least one of quality of the one or more products of a brand, the range of designs available in the brand, the number of merchants selling products by the brand and quality and financials of the merchants selling the products.