Google C.E.O. revealed this ...
Sergey, for example, has been looking at new ways of doing search quality, a new math around that.
in an interview a few months ago.
This March 2005 Patent, relealed potential new directions in Google ALGOs.
There appears to be changes occurring now and predictions for massive changes in a few months....
It will probably be based on this....How many of these suggestions are being implemented with the current update?
Information retrieval based on historical data
Quote:
| [0099] 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. |
Quote:
| [0100] 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. |
Quote:
| [0101] Also, or alternatively, the age, or other information, regarding a name server associated with a domain may be used to predict the legitimacy of the domain. A "good" name server may have a mix of different domains from different registrars and have a history of hosting those domains, while a "bad" name server might host mainly pornography or doorway domains, domains with commercial words (a common indicator of spam), or primarily bulk domains from a single registrar, or might be brand new. The newness of a name server might not automatically be a negative factor in determining the legitimacy of the associated domain, but in combination with other factors, such as ones described herein, it could be. |
[0102] In summary, search engine 125 may generate (or alter) a score associated with a document based, at least in part, on information relating to a legitimacy of a domain associated with the document.
[0103] Ranking History
Quote:
| [0104] According to an implementation consistent with the principles of the invention, information relating to prior rankings of a document may be used to generate (or alter) a score associated with the document. For example, search engine 125 may monitor the time-varying ranking of a document in response to search queries provided to search engine 125. Search engine 125 may determine that a document that jumps in rankings across many queries might be a topical document or it could signal an attempt to spam search engine 125. |
Quote:
| [0105] Thus, the quantity or rate that a document moves in rankings over a period of time might be used to influence future scores assigned to that document. In one implementation, for each set of search results, a document may be weighted according to its position in the top N search results. For N=30, one example function might be [((N+1)-SLOT)/N].sup.4. In this case, a top result may receive a score of 1.0, down to a score near 0 for the Nth result. |
Quote:
| [0106] A query set (e.g., of commercial queries) can be repeated, and documents that gained more than M % in the rankings may be flagged or the percentage growth in ranking may be used as a signal in determining scores for the documents. For example, search engine 125 may determine that a query is likely commercial if the average (median) score of the top results is relatively high and there is a significant amount of change in the top results from month to month. Search engine 125 may also monitor churn as an indication of a commercial query. For commercial queries, the likelihood of spam is higher, so search engine 125 may treat documents associated therewith accordingly. |
Quote:
| [0107] In addition to history of positions (or rankings) of documents for a given query, search engine 125 may monitor (on a page, host, document, and/or domain basis) one or more other factors, such as the number of queries for which, and the rate at which (increasing/decreasing), a document is selected as a search result over time; seasonality, burstiness, and other patterns over time that a document is selected as a search result; and/or changes in scores over time for a URL-query pair. |
Quote:
| [0108] In addition, or alternatively, search engine 125 may monitor a number of document (e.g., URL) independent query-based criteria over time. For example, search engine 125 may monitor the average score among a top set of results generated in response to a given query or set of queries and adjust the score of that set of results and/or other results generated in response to the given query or set of queries. Moreover, search engine 125 may monitor the number of results generated for a particular query or set of queries over time. If search engine 125 determines that the number of results increases or that there is a change in the rate of increase (e.g., such an increase may be an indication of a "hot topic" or other phenomenon), search engine 125 may score those results higher in the future. |
Quote:
| [0109] 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. |
Quote:
| [0110] It may be possible for search engine 125 to make exceptions for documents that are determined to be authoritative in some respect, such as government documents, web directories (e.g., Yahoo), and documents that have shown a relatively steady and high rank over time. For example, if an unusual spike in the number or rate of increase of links to an authoritative document occurs, then search engine 125 may consider such a document not to be spam and, thus, allow a relatively high or even no threshold for (growth of) its rank (over time). |
Quote:
| [0111] In addition, or alternatively, search engine 125 may consider significant drops in ranks of documents as an indication that these documents are "out of favor" or outdated. For example, if the rank of a document over time drops significantly, then search engine 125 may consider the document as outdated and score the document accordingly. |
[0112] In summary, search engine 125 may generate (or alter) a score associated with a document based, at least in part, on information relating to prior rankings of the document.
[0113] User Maintained/Generated Data
Quote:
| [0114] According to an implementation consistent with the principles of the invention, user maintained or generated data may be used to generate (or alter) a score associated with a document. For example, search engine 125 may monitor data maintained or generated by a user, such as "bookmarks," "favorites," or other types of data that may provide some indication of documents favored by, or of interest to, the user. Search engine 125 may obtain this data either directly (e.g., via a browser assistant) or indirectly (e.g., via a browser). Search engine 125 may then analyze over time a number of bookmarks/favorites to which a document is associated to determine the importance of the document. |
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thanks for your information