The dates that links appear can also be used to detect “spam,” where owners of documents or their colleagues create links to their own document for the purpose of boosting the score assigned by a search engine. A typical, “legitimate” document attracts back links slowly. A large spike in the quantity of back links may signal a topical phenomenon (e.g., the CDC web site may develop many links quickly after an outbreak, such as SARS), or signal attempts to spam a search engine (to obtain a higher ranking and, thus, better placement in search results) by exchanging links, purchasing links, or gaining links from documents without editorial discretion on making links. Examples of documents that give links without editorial discretion include guest books, referrer logs, and “free for all” pages that let anyone add a link to a document.
15. The method of claim 1, wherein the one or more types of history data includes information relating to how often the document is selected when the document is included in a set of search results; and wherein the generating a score includes: determining an extent to which the document is selected over time when the document is included in a set of search results, and scoring the document based, at least in part, on the extent to which the document is selected over time when the document is included in the set of search results.
25. The method of claim 22, wherein the determining behavior of links associated with the document includes monitoring at least one of time-varying behavior of links associated with the document, how many links associated with the document appear or disappear during a time period, and whether there is a trend toward appearance of new links associated with the document versus disappearance of existing links associated with the document.
29. The method of claim 26, wherein the scoring the document includes: determining an age of each link pointing to the document, determining an age distribution associated with the links based on the ages of the links, and scoring the document based, at least in part, on the age distribution associated with the links.
30. The method of claim 1, wherein the one or more types of history data includes information relating to a manner in which anchor text changes over time; and wherein the generating a score includes: identifying a change in anchor text associated with a link to the document, and scoring the document based, at least in part, on the change in anchor text associated with a link to the document.
48. The method of claim 1, wherein the one or more types of history data includes information relating to growth profiles of anchor text; and wherein the generating a score includes: determining a growth profile of anchor text associated with one or more links to the document, and scoring the document based, at least in part, on the growth profile of anchor text associated with one or more links to the document.
58. The method of claim 57, further comprising: determining longevity of the linkage data; deriving an indication of content update for a linking document providing the linkage data; and adjusting the ranking of the linked document based on the longevity of the linkage data and the indication of content update for the linking document.
63. The method of claim 62, wherein adjusting the ranking includes penalizing the ranking if the link churn is above a threshold.
 Search engine 125 may use the inception date of a document for scoring of the document. For example, it may be assumed that a document with a fairly recent inception date will not have a significant number of links from other documents (i.e., back links). For existing link-based scoring techniques that score based on the number of links to/from a document, this recent document may be scored lower than an older document that has a larger number of links (e.g., back links). When the inception date of the documents are considered, however, the scores of the documents may be modified (either positively or negatively) based on the documents’ inception dates.
 Consider the example of a document with an inception date of yesterday that is referenced by 10 back links. This document may be scored higher by search engine 125 than a document with an inception date of 10 years ago that is referenced by 100 back links because the rate of link growth for the former is relatively higher than the latter. While a spiky rate of growth in the number of back links may be a factor used by search engine 125 to score documents, it may also signal an attempt to spam search engine 125. Accordingly, in this situation, search engine 125 may actually lower the score of a document(s) to reduce the effect of spamming.
 Thus, according to an implementation consistent with the principles of the invention, search engine 125 may use the inception date of a document to determine a rate at which links to the document are created (e.g., as an average per unit time based on the number of links created since the inception date or some window in that period). This rate can then be used to score the document, for example, giving more weight to documents to which links are generated more often.
 These dates may be determined by search engine 125 during a crawl or index update operation. Using this date as a reference, search engine 125 may then monitor the time-varying behavior of links to the document, such as when links appear or disappear, the rate at which links appear or disappear over time, how many links appear or disappear during a given time period, whether there is trend toward appearance of new links versus disappearance of existing links to the document, etc.
 Links may be weighted in other ways. For example, links may be weighted based on how much the documents containing the links are trusted (e.g., government documents can be given high trust). Links may also, or alternatively, be weighted based on how authoritative the documents containing the links are (e.g., authoritative documents may be determined in a manner similar to that described in U.S. Pat. No. 6,285,999). Links may also, or alternatively, be weighted based on the freshness of the documents containing the links using some other features to establish freshness (e.g., a document that is updated frequently (e.g., the Yahoo home page) suddenly drops a link to a document).
 Alternatively, if the content of a document changes such that it differs significantly from the anchor text associated with its back links, then the domain associated with the document may have changed significantly (completely) from a previous incarnation. This may occur when a domain expires and a different party purchases the domain. Because anchor text is often considered to be part of the document to which its associated link points, the domain may show up in search results for queries that are no longer on topic. This is an undesirable result.
 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.
 In addition, or alternatively, search engine 125 may monitor the ranks of documents over time to detect sudden spikes in the ranks of the documents. A spike may indicate either a topical phenomenon (e.g., a hot topic) or an attempt to spam search engine 125 by, for example, trading or purchasing links. Search engine 125 may take measures to prevent spam attempts by, for example, employing hysteresis to allow a rank to grow at a certain rate. In another implementation, the rank for a given document may be allowed a certain maximum threshold of growth over a predefined window of time. As a further measure to differentiate a document related to a topical phenomenon from a spam document, search engine 125 may consider mentions of the document in news articles, discussion groups, etc. on the theory that spam documents will not be mentioned, for example, in the news. Any or a combination of these techniques may be used to curtail spamming attempts