Google Inc.

Huican Zhu

Anurag Acharya

Howard Bradley Gobioff

Jeffrey Adgate Dean

Sanjay Ghemawat

Bwolen Po-Jen Yang

Maximilian Ibel

Max Ibel

Jun Wu

Hongjun Zhu

Systems and method are provided for setting a respective reuse flag for a corresponding document in a plurality of documents based on a query-independent score associated with the corresponding document. A document crawling operation is performed on the plurality of documents in accordance with the reuse flag for respective documents in the plurality of documents. This document crawling operation includes reusing a previously downloaded version of a respective document in the plurality of documents instead of downloading a current version of the respective document from a host computer in accordance with a determination that the reuse flag associated with the respective document meets a predefined criterion.

Document reuse in a search engine crawler

Provided is a method and system for indexing documents in a collection of linked documents. A link log, including one or more pairings of source documents and target documents is accessed. A sorted anchor map, containing one or more target document to source document pairings, is generated. The pairings in the sorted anchor map are ordered based on target document identifiers.

Anchor tag indexing in a web crawler system

Document identification tags are assigned to documents to be added to a collection of documents. Based on query-independent information about a new document, a document identification tag is assigned to the new document. The document identification tag so assigned is used in the indexing of the new document. When a list of document identification tags are produced by an index in response to a query, the list is approximately ordered with respect to a measure of query-independent relevance. In some embodiments, the measure of query-independent relevance is related to the connectivity matrix of the World Wide Web. In other embodiments, the measure is related to the recency of crawling. In still other embodiments, the measure is a mixture of these two. The provided systems and methods allow for real-time indexing of documents as they are crawled from a collection of documents.

Assigning document identification tags

A search engine crawler includes a scheduler for determining which documents to download from their respective host servers. Some documents, known to be stable based on one or more record from prior crawls, are reused from a document repository. A reuse flag is set in a scheduler record that also contains a document identifier, the reuse flag indicating whether the document should be retrieved from a first database, such as the World Wide Web, or a second database, such as a document repository. A set of such scheduler records are used during a crawl by the search engine crawler to determine which database to use when retrieving the documents identified in the scheduler records.

A search engine crawler includes a distributed set of schedulers that are associated with one or more segments of document identifiers (e.g., URLs) corresponding to documents on a network (e.g., WWW). Each scheduler handles the scheduling of document identifiers (for crawling) for a subset of the known document identifiers. Using a starting set of document identifiers, such as the document identifiers crawled (or scheduled for crawling) during the most recent completed crawl, the scheduler removes from the starting set those document identifiers that have been unreachable in each of the last X crawls. Other filtering mechanisms may also be used to filter out some of the document identifiers in the starting set. The resulting list of document identifiers is written to a scheduled output file for use in a next crawl cycle.

Scheduler for search engine crawler

Systems and methods of classifying user input are disclosed. The user input can be, for example, in the form of Roman characters. An ambiguous word (e.g., a word that is a non-pinyin word written in Roman characters and a valid pinyin word) can be identified in the user input. Contextual words (e.g., words adjacent to the ambiguous word) are classified as a pinyin context or a non-pinyin context. The ambiguous word is classified based on the context of the contextual words.

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San Jose, CA, United States of America

Huican Zhu