Abstract: A method, system and a computer program product are provided for making product recommendations to improve a user's personal brand by using the symbolic meanings and utilities of products and a user's brand perceptions along with users input of a desired personal brand imagery to output a set of products that are optimized to help users bridge the gaps between their desired and actual self-brand, thereby enabling a user to navigate products that shape their personal imagery.

Abstract: Mechanisms are provided to implement a brand personality inference engine. The mechanisms receive crowdsource information and extract features associated with a brand from the crowdsource information. The crowdsource information comprises natural language content submitted by a plurality of providers to a crowdsource information source. The mechanisms analyze features associated with the brand in accordance with a brand personality model configured to predict a brand personality for the brand based on the features associated with the brand. The mechanisms generate an inferred brand personality data structure, representing a perceived brand personality of providers providing the crowdsource information, and output an output indicating aspects of the perceived brand personality based on the inferred brand personality data structure.

Abstract: Mechanisms are provided to implement a brand personality perception gap assessment engine. The mechanisms receive an inferred brand personality for a specified brand. The mechanisms further receive an intended brand personality for the specified brand. The mechanisms calculate at least one gap between the inferred brand personality and the intended brand personality. The mechanisms output an output indicating aspects of the at least one gap.

Abstract: Mechanisms are provided to implement a brand comparison engine. The mechanisms receive a request to compare brand personalities of a first specified brand and a second specified brand and obtain a first brand personality scale associated with the first specified brand and a second brand personality scale associated with the second specified brand. The mechanisms calculate at least one gap value indicating a difference between at least one personality trait in the first brand personality scale and a corresponding at least one personality trait in the second brand personality scale. The mechanisms also output an output indicating an aspect of the at least one gap based on the calculation.

Abstract: Exemplary embodiments described herein are directed to systems and methods that estimate a user's affect and communication preferences from presence data. The exemplary embodiments use a small set of features derived from a user's recent high level presence states. Exemplary embodiments also use features from broader classes of presence data. Utilizing features from a combination of presence data and recent presence states may provide improvement over estimates that users are able to make themselves. The exemplary embodiments further consider cost, burden on the user, and privacy issues in estimating affect and communication preferences.

Abstract: Exemplary embodiments described herein are directed to systems and methods that estimate a user's affect and communication preferences from presence data. The exemplary embodiments use a small set of features derived from a user's recent high level presence states. Exemplary embodiments also use features from broader classes of presence data. Utilizing features from a combination of presence data and recent presence states may provide improvement over estimates that users are able to make themselves. The exemplary embodiments further consider cost, burden on the user, and privacy issues in estimating affect and communication preferences.