Abstract: Disclosed is a method of ranking linkable nodes based on intrinsic scores assigned to the nodes. In one embodiment, a computer-implemented method includes the steps of analyzing each document with respect to at least one criterion comprising the frequency of occurrence of a search token, and assigning an intrinsic score to each document based on the analysis, the intrinsic score measuring at least one intrinsic property of the respective document and not its relations to other documents; identifying links between the documents; and using a processor, generating a ranking score for each document based at least in part on the intrinsic scores of nodes linked therewith.

Abstract: Search systems and methods address the subjective nature of the relevancy of matches to users' queries through the use of readability formulae. As a result, the documents are ranked by relevance not only to user queries, but specifically to the user. In one approach, the searchable web (or a searchable corpus of documents) is categorized on one or more servers. Each document is designated by reading level or other parameter(s) relevant to the user's reading ability. In one embodiment, searching is carried out utilizing the user's search query, and documents are ranked based on relevance to the query and on their degree of readability to the user—e.g., the degree to which the contents of each document correspond to the user's reading level. Advertisement displays may be targeted to both the search tokens entered and the user's age as determined from his reading level, rendering search-related advertisements significantly more effective in reaching their intended audiences.