Abstract: The current invention provides a method, system and computer program product for designing a catalog with optimized placement of items. Past user transactions are used to estimate the effect of nature and placement of an item on the response of users to the catalogs in terms of items clicked on or items purchased. These estimations are used to optimize the placement of items in a catalog in order to maximize the gains for a merchant specified objective, which can be in terms of revenues, sales or the number of clicks. Various stochastic and deterministic optimization functions are used for the purpose of optimization.

Abstract: An unsupervised decision tree is constructed, involving the data records or patterns that do not posses any class labels. The objective of clustering or segmenting the data set is to discover subsets of data records that possess homogeneous characteristics. In the context of clustering, namely grouping or segmenting data sets without any supervised information, an interpretable decision tree is recognized as beneficial in various contexts such as customer profiling, text mining, and image and video categorization.

Abstract: A user's preference structure in respect of alternative “objects” with which the user is presented is caputured in a multi-attribute utility function. The user ranks these competing objects in order of the user's relative preference for such objects. A utility function that defines the user's preference structure is provided as output on the basis of this relative ranking. This technique can be used to assist a buyer in selecting between multi-attribute quotes or bids submitted by prospective suppliers to the buyer.

Abstract: A method, system and computer program product for generating a personalized list of items for a user are disclosed. The method includes the steps of storing inter-item relationships, adaptively identifying and storing users' interests based on behavioral patterns of users and generating a personalized list of items for a user, based on the user's stored interests and the inter-item relationships. The method optionally includes the additional steps of identifying and storing attributes of items and defining the inter-item relationships on the basis of the degree of similarity between item attributes. A user's interests can also be categorized on the basis of item attributes. The system and computer program product disclosed are for performing the steps of the foregoing method.