A typical day of million web users all over the world starts with a simple query. The quest for information on a particular topic drives them to search for it, and in the pursuit of their info the terms they supply for queries varies from person to person depending on the knowledge they have. With a vast collection of documents available on the web universe it is the onus of the retrieval system to return only those documents that are relevant and satisfy the user’s search requirements. The document mismatch problem is resolved by appending extra query terms to the original query which improves the retrieval performance. The addition of terms tends to minimize the bridging-gap between the documents and queries. In this thesis, a brief study is done on the reformulation of queries, along with methods of calculating the relevancy of candidate terms for query expansion by using several ranking algorithms, term weighting algorithms and feedback processes involving evaluations. Comparisons of various methods based on their efficiencies are also discussed. On the whole a consolidated report of query expansion in general is given.