1. A computer-implemented method to query a set of documents based on multiple relevance value types, the method comprising: providing, for each document in the set, a summary representing the respective document, wherein providing the summary comprises, for each document, identifying content marked by hierarchical tags and generating the summary from the content marked by higher-order hierarchical tags; parsing the set of documents using a received set of search terms in order to calculate, for each document in the set, a first relevance value based on the summary of the respective document and not based on the respective document itself; parsing, from the set of documents and using the received set of search terms, only a subset of documents having the highest first relevance values in order to calculate, by operation of one or more computer processors and for each document in the subset, a second relevance value based on the respective document itself and not based on the summary of the respective document, wherein the subset excludes at least one document in the set and for which a second relevance value is not calculated, thereby avoiding a processing cost associated with calculating the second relevance value for the at least one document in the set; and providing query results comprising documents from the subset that have the highest second relevance values, regardless of the first relevance value of any document in the set, wherein the query results exclude the at least one document in the set and at least one document in the subset.
1. A computer-implemented method to query a set of documents based on multiple relevance value types, the method comprising: providing, for each document in the set, a summary representing the respective document, wherein providing the summary comprises, for each document, identifying content marked by hierarchical tags and generating the summary from the content marked by higher-order hierarchical tags; parsing the set of documents using a received set of search terms in order to calculate, for each document in the set, a first relevance value based on the summary of the respective document and not based on the respective document itself; parsing, from the set of documents and using the received set of search terms, only a subset of documents having the highest first relevance values in order to calculate, by operation of one or more computer processors and for each document in the subset, a second relevance value based on the respective document itself and not based on the summary of the respective document, wherein the subset excludes at least one document in the set and for which a second relevance value is not calculated, thereby avoiding a processing cost associated with calculating the second relevance value for the at least one document in the set; and providing query results comprising documents from the subset that have the highest second relevance values, regardless of the first relevance value of any document in the set, wherein the query results exclude the at least one document in the set and at least one document in the subset. 10. The computer-implemented method of claim 1 , wherein the first relevance value of each document in the set is of a first relevance value type, wherein the second relevance value of each document in the subset is of a second relevance value type different from the first relevance value type, wherein the second relevance value of each document in the subset more accurately characterizes the respective document than the first relevance value of the respective document in the subset, wherein the first relevance value of each document in the subset is different from the second relevance value of the respective document in the subset.