Google Inc.

Apple Inc.

Steven D Baker

Paul Haahr

Trystan G Upstill

Srinivasan Venkatachary

Simon Tong

Uri N Lerner

Nitin Kumar Gupta

Elizabeth Caroline Cranfill

Amit Singhal

John Ogden Lamping

Oleksandr Grushetskyy

Yonghui Wu

Michael E Flaster

Dimitra Papachristou

Craig Michael Federighi

Andre Souza Dos Santos

Grant R Paul

Nathan De Vries

Bryan Christopher Horling

Ryan S Dixon

Johnnie B Manzari

Vignesh Jagadeesh

Maureen Heymans

Marco Zuliani

James Nicholas Jones

Matthias Paulik

Neil Gareth Crane

Viktor Miladinov

Matthew K Gray

Jeffrey A Brasket

Vincent M Lane

Ke Yang

Vinay Sharma

Brandon J Corey

Xin Wang

Guillaume Borios

Hang Zhao

Diego Federici

Nicholas D Lupinetti

Anand Shukla

Kellie L Albert

Yi Liu

Per Bjornsson

Robert Andrew Brennan

Lingkun Chu

Massimiliano Ciaramita

Hadar Shemtov

Ioannis Tsochantaridis

Kushal Tayal

Namrata U Godbole

Grant Dasher

Vishnu Priya Natchu

Evan M Martin

Preyas Popat

Pulah J Shah

Matthias Dantone

Eric Steinlauf

Ron C Santos

Kayur Dushyant Patel

Thomas Deselaers

Yang Zhao

Aya Siblini

Ngoc Hong Pham

Samer Hassan Hassan

Chen Ye

Xishuo Liu

Sebastien V Marineau-mes

Ionut Georgescu

Derek Kisman

Bilgenhan Uygar Oztekin

Francisco Alvaro Munoz

Rajen Chatterjee

Amittai Axelrod

Siyang Tang

Jennifer Pon Chen

Sebastien V Marineau-Mes

Guangyu Zhong

Adam Huff Bradford

Mallika Priya Khullar

The present disclosure generally relates to methods and user interfaces for managing visual content at a computer system. In some embodiments, methods and user interfaces for managing visual content in media are described. In some embodiments, methods and user interfaces for managing visual indicators for visual content in media are described. In some embodiments, methods and user interfaces for inserting visual content in media are described. In some embodiments, methods and user interfaces for identifying visual content in media are described. In some embodiments, methods and user interfaces for translating visual content in media are described. In some embodiments, methods and user interfaces for translating visual content in media are described. In some embodiments, methods and user interfaces for managing user interface objects for visual content in media are described.

User interfaces for managing visual content in media

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for context scoring adjustments for candidate answer passages. In one aspect, a method includes scoring candidate answer passages. For each candidate answer passage, the system determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading to which the candidate answer passage is subordinate; determines a context score based, at least in part, on the heading vector; and adjusts answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score. The system then selects an answer passage from the candidate answer passages based on the adjusted answer scores.

Context scoring adjustments for answer passages

An embedding associated with a query comprising one or more query terms is determined to be not stored in memory. An embedding is generated for the one or more query terms. One or more web documents that are similar to the generated embedding are determined. One or more content cards associated with the one or more web documents that are determined to be similar to the generated embedding are provided in a content feed.

Golden embeddings

A curation score associated with an entity is determined. A good interest probability value associated with the entity is determined. A content feed for a user that includes one or more web documents is generated based in part on the curation score and the good interest probability value.

Validating interests for a search and feed service

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scoring candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query that seeks an answer response and data identifying resources determined to be responsive to the query; for a subset of the resources: receiving candidate answer passages; determining, for each candidate answer passage, a query term match score that is a measure of similarity of the query terms to the candidate answer passage; determining, for each candidate answer passage, an answer term match score that is a measure of similarity of answer terms to the candidate answer passage; determining, for each candidate answer passage, a query dependent score based on the query term match score and the answer term match score; and generating an answer score that is a based on the query dependent score.

Scoring candidate answer passages

Methods and systems for providing an image with an answer to a question query. A method receiving a first query that is determined to be a question query; generating a second query form the first query; causing a search of a plurality of resources of a first corpus using the second query as input, wherein the first corpus of resources are resources that include images and textual data rendered with the images; receiving data indicating a set of resources determined to be responsive to the second query; causing a search for images in the set of resources; selecting, from the set of images and based in part on the search for images in the first set of resources, an image to be provided with the answer in response to the query; and providing, by the data processing apparatus, and with the answer, the image in response to the first query.

Images for query answers

A stopword detection component detects stopwords (also stop-phrases) in search queries input to keyword-based information retrieval systems. Potential stopwords are initially identified by comparing the terms in the search query to a list of known stopwords. Context data is then retrieved based on the search query and the identified stopwords. In one implementation, the context data includes documents retrieved from a document index. In another implementation, the context data includes categories relevant to the search query. Sets of retrieved context data are compared to one another to determine if they are substantially similar. If the sets of context data are substantially similar, this fact may be used to infer that the removal of the potential stopword(s) is not material to the search. If the sets of context data are not substantially similar, the potential stopword can be considered material to the search and should not be removed from the query.

Locating meaningful stopwords or stop-phrases in keyword-based retrieval systems

A system and method for generating query refinement suggestions may include collecting refinement data for at least one received source query. The collected refinement data is then clustered to form at least one cluster. At least one potential refinement query suggestion is identified from the refinement data within the at least one cluster.

Systems and methods for providing search query refinements

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query data identifying resources determined to be responsive to the query; for each resource in a top-ranked subset of the resources: identifying a plurality of passage units in the resource; applying a set of passage unit selection criterion to the passage units, each passage unit selection criterion specifying a condition for inclusion of a passage unit in a candidate answer passage, wherein a first subset of passage unit selection criteria applies to structured content and a second subset of passage unit selection criteria applies to unstructured content; and generating, from passage units that satisfy the set of passage unit selection criterion, a set of candidate answer passages.

Candidate answer passages

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying implicit question queries. In one aspect, a method includes receiving a query in unstructured form, comparing terms of the query to query templates, determining, based on the comparison, a match of the query terms to a first query template, wherein the first query template is not determined to be indicative of a question query, determining, based on the first query template, a second query template, and determining that the query is an implicit question query in response to the second query template being indicative of a question queries.

Implicit question query identification

A system and method for providing search query refinements are presented. A stored query and a stored document are associated as a logical pairing. A weight is assigned to the logical pairing. The search query is issued and a set of search documents is produced. At least one search document is matched to at least one stored document. The stored query and the assigned weight associated with the matching at least one stored document are retrieved. At least one cluster is formed based on the stored query and the assigned weight associated with the matching at least one stored document. The stored query associated with the matching at least one stored document are scored for the at least one cluster relative to at least one other cluster. At least one such scored search query is suggested as a set of query refinements.

System and method for providing search query refinements

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San Francisco, CA, United States of America

Steven D Baker