The k-Means algorithm uses a similarity metric of distance between a record and a cluster centroid. If the attributes of the records are not quantitative but categorical in nature, such as Income_level with values {low, medium, high} or Married with values {Yes, No} or State_of_residence with values {Alabama, Alaska, ..., Wyoming}, then the distance metric is not meaningful. Define a more suitable similarity metric that can be used for clustering data records that contain categorical data.