Abstract
In the history of information-seeking, the intention of a query and the posed query have some level of distance between them. Because human query-responders are innately connected to times and trends and have the ability to understand natural language and human intention, they have often been the idealistic sources of knowledge-direction. As the quantity of depth of knowledge of humanity grows, technological systems have sought to utilize natural language, both spoken and written, as a format of accepted queries. Modern works seek to improve such systems utilizing distance-metrics of literal queries to understood questions with maps to knowledge-bases. However, these methods do not often take into account the value of information in terms of query interpretation for mapping and as such may have identifiable limitations compared with human responders. In this paper, a model for information value is proposed and existing works in speech and query recognition are discussed relative to their considerations of information value.