?..the history data may include data relating to: document inception dates; document content updates/changes; query analysis; link-based criteria; anchor text (e.g., the text in which a hyperlink is embedded, typically underlined or otherwise highlighted in a document); traffic; user behavior; domain-related information; ranking history; user maintained/generated data (e.g., bookmarks); unique words, bigrams, and phrases in anchor text; linkage of independent peers; and/or document topics. These different types of history data are described in additional detail below. In other implementations, the history data may include additional or different kinds of data.
Individuals who attempt to deceive (spam) search engines often use throwaway or ?doorway? domains and attempt to obtain as much traffic as possible before being caught. Information regarding the legitimacy of the domains may be used by search engine 125 when scoring the documents associated with these domains.
Certain signals may be used to distinguish between illegitimate and legitimate domains. For example, domains can be renewed up to a period of 10 years. Valuable (legitimate) domains are often paid for several years in advance, while doorway (illegitimate) domains rarely are used for more than a year. Therefore, the date when a domain expires in the future can be used as a factor in predicting the legitimacy of a domain and, thus, the documents associated therewith.
Also, or alternatively, the domain name server (DNS) record for a domain may be monitored to predict whether a domain is legitimate. The DNS record contains details of who registered the domain, administrative and technical addresses, and the addresses of name servers (i.e., servers that resolve the domain name into an IP address). By analyzing this data over time for a domain, illegitimate domains may be identified. For instance, search engine 125 may monitor whether physically correct address information exists over a period of time, whether contact information for the domain changes relatively often, whether there is a relatively high number of changes between different name servers and hosting companies, etc. In one implementation, a list of known-bad contact information, name servers, and/or IP addresses may be identified, stored, and used in predicting the legitimacy of a domain and, thus, the documents associated therewith.
I'll tell you that it is in some of Google's patents for search algorithms - not that private whois will hurt you but more so that public can help a bit.
