When retrieving documents for a search query, a simplistic approach that ranks the most relevant documents highest will leave users completely unsatisfied if it incorrectly interprets the query. Incorrect interpretation is an inevitable possibility when dealing with ambiguous queries, which in some experiments were shown to represent over 16% of all queries. To address this we can apply a topic modeling algorithm to the fetched search results and then use a reordering algorithm to ensure we highly rank both relevant documents and topics with a high probability of being in different topics.