Multidimensional search refers to the process of finding information across multiple dimensions or attributes, rather than just one. This approach is commonly used in databases and search engines to improve the accuracy and relevance of search results. For example, a user might search for restaurants based on criteria like location, cuisine type, and price range, allowing for a more tailored experience. In multidimensional search, data is often organized in a way that allows for complex queries. Techniques such as vector space models or k-nearest neighbors can be employed to analyze and retrieve data efficiently. This method enhances user experience by providing results that better match their specific needs.