Information spaces, such as the Internet, enterprise networks, etc., allow widespread access to large collections of information. For example, users commonly use search engines to locate and select their desired information on the Internet. Many entities, such as businesses, individuals, government organizations, etc., now use the Internet to publish information, advertise goods and services that they provide. Publishers have an interest in ensuring that theft content can be easily located. Also, users performing searches have an interest in locating items that are most relevant to their search.
Depending on the information space and how it is organized, a user's search may seek items containing varying types of information. Special tags may be placed on items to permit the user to make use of those tags in specifying a query to a search engine. The tags may refer to various properties of items, such as the date of publication, the size of the items, the number of times the items have been accessed, etc.
In conventional search engines, the user that is searching must guess the correct combination of keywords for a desired concept. Content provider also must guess as to how the document will be searched. People are searching for words, not ideas, in the prior art. This “guessing problem” represents an issue for both content users and content providers. A variety of words can map to ideas in multiple and non-unique ways making tagging and searching based on keywords difficult. However, a combination of words is unlikely to be the same between two users. Search engines operate on literal matching in actual content or tags. Accordingly, concept or semantic matching of search engines is still poor. Unfortunately, even with the use of such tags, conventional search engines simply match keywords and are ineffective at leveraging the true meaning or semantics of the search. Conventional search engines are very ineffective at leveraging the meaning that is inherent in content items. Indeed, because, for many items, item content is expressed in natural language with no convention or structure governing the meaning of the items, search engines are, in general, unable to locate items based on their meaning or significance.
The conventional search interface consisting of a query box and a list of search results provides a relatively poor user experience for navigation of information spaces. Furthermore, attempts at providing enhanced search, such as faceted metadata, tags, etc., have failed to significantly improve the search experience. The use and maintenance of metadata and tags is difficult to produce and can be of varying quality.