Data has been used in determining the users’ preferences on their search results. Many existing personalized web search systems are based clickthrough data to determine users’ preferences. Mine document preferences from clickthrough data. A spying technique together with a novel voting procedure to determine user preferences. More recently, Introduced an effective approach to predict users’ conceptual preferences from clickthrough data for personalized query suggestions. Search queries can be classified as content or location queries. Examples of location queries are “hong kong hotels”, “museums in london” and “virginia historical sites”. A classifier to classify geo and nongeo queries. It was found that a significant number of queries were location queries focusing on location information. In order to handle the queries that focus on location information, a number of location-based search systems designed for location queries have been proposed. A location-based search system for web documents. Location information were extracted from the web documents, which was converted into latitude-longitude pairs. When a user submits a query together with a latitude longitude pair, the system creates a search circle centered at the specified latitude-longitude pair and retrieves documents containing location information within the search circle.