One of the largest challenges for a recommender system is building a ranking of “quality” or “relevance” in situations where these features cannot be observed directly. These models are often trained on various types of survey data, including Likert-scale quality ratings or pairwise comparison surveys, but there has been little work detailing the efficiency of these techniques for eliciting qua...

Surveys are an important tool for researchers. Survey attributes are typically discrete data measured on a Likert scale. Collected responses from the survey contain an enormous amount of data. It is increasingly important to develop powerful means for clustering such data and knowledge extraction that could help in decision-making. The process of clustering becomes complex if the number of surv...