Joshua Correa

Affiliation: Unknown

Papers

  • Improving Recommendation Relevance by simulating User Interest

    Most if not all on-line item-to-item recommendation systems rely on estimation of a distance like measure (rank) of similarity between items. For on-line recommendation systems, time sensitivity of this similarity measure is extremely important. We observe that recommendation "recency" can be straightforwardly and transparently maintained by iterative reduction of ranks …