In the first half of the talk, I will discuss data mining technologies that can result in better browsing and searching. Consider the problem of merging documents from different categorizations (taxonomies) into a single master categorization. Current classifiers ignore the implicit similarity information present in the source categorizations. I will show that by incorporating this information into the classification model, classification accuracy can be substantially improved [1]. Next, I will demonstrate novel search technology that treats numbers as first-class objects, and thus yields dramatically better results than current Web search engines when searching over product descriptions or other number-rich documents [2].