Google Inc.

Arash Baratloo

Vivek Raghunathan

Ashish Agarwal

Chiu Wah Kelvin So

Qicheng Ma

Alice S Tull

Nicholas Chamandy

Emmanuel Christophe

Japinder Singh

Sandeep Singhal

Wangyuan Zhang

Sangho Yoon

Pramod Gaud

Guangda Lai

Zhifan Zhang

Gael Hatchue Njouyep

Monika Hildegard Henzinger

Robert J Stets, Jr

Zhe Qian

Keith H Randall

Eric Christopher Rollins

Wilburt Labio

Ming-Yee Iu

Benjamin J Young

Daniel Virabott Phang

A method includes receiving data objects, determining a predicted lifespan of each data object, and instantiating multiple shard files. Each shard file has an associated predicted lifespan range. The method also includes writing each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object and storing the shard files in a distributed system. The method also includes determining whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file. For each stored shard file satisfying the compaction criteria, the method also includes compacting the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file.

Packing objects by predicted lifespans in cloud storage

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for serving advertisements based on partial queries. In one aspect, a method includes receiving a request for advertisements that specifies a set of query suggestions. The query suggestions are ranked based, at least in part on a probability of each query suggestion being selected by a user that input the partial query. A proper subset of the query suggestions is selected and includes a highest ranked query suggestion based on the ranking and one or more query suggestions of the set of query suggestions that is at least one of a revision of the highest ranked query suggestion or refers to a same topic as the highest ranked query suggestion. One or more advertisements are identified for each query suggestion of the proper subset. Data specifying the identified advertisements are provided.

Serving advertisements based on partial queries

Methods, systems, and apparatus, including computer programs encoded on computer storage media are provided. An example method includes receiving user input in a control, for example, one associated with a search engine. The user input includes a series of input characters that when completed would form a completed user request. The method further includes, while receiving the user input, evaluating the characters to identify completions for the completed request. The method further includes identifying, by one or more processors, a content item associated with the one or more completions and identifying display data associated with the content item for transmission to the user along with one or more completions in response to receiving the user input.

Selecting and presenting content relevant to user input

An advertiser may be provided with fast and accurate estimates of the future cost and/or performance information for one or more actual or hypothetical ads (generally referred to as 'proto-ads'). Past auction information may be used to simulate auctions that the proto-ad would have competed in. The proto-ad may then participate in a 'replay' of such past auctions.

Estimating cost and/or performance information for an advertisement in an advertising system

Methods, systems, and apparatus, including computer programs encoded on computer storage media are provided. One example method includes receiving a textual input that forms a part of a user request, the textual input in the form of a prefix that when complete constitutes the request. The method further includes identifying completions based on the prefix, determining one or more content items associated with each completion, computing initial scores including a score for each content item-completion pair including determining a likelihood that a given completion represents the request and a quality of the content item as compared to the completion, computing final scores including scores for each prefix-content item pair using the initial scores, computing a bid for each content item, running an auction to select a content item based on the bids and final scores, and identifying display data associated with the selected content item.

Dynamically selecting and presenting content relevant to user input

A set of one or more candidate parameters associated with a content item is identified. A subset of the one or more candidate parameters is determined. Performance statistics associated with the one or more candidate parameters in the subset are monitored, and the set of one or more candidate parameters or the subset of the one or more candidate parameters are modified based on the performance statistics.

Content item parameter filter

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Mountain View, CA, United States of America

Arash Baratloo