Apple Inc.

Cloudmark, Inc.

Topsy Labs, Inc.

Vipul Ved Prakash

Rishab Aiyer Ghosh

Lun Cui

Gaurav Kapoor

Umesh Suresh Vaishampayan

Andrew H Vyrros

John Martin Hörnkvist

Abhradeep Guha Thakurta

Arnaud Legendre

David Salim

Steven Duplinsky

Julien Freudinger

Julien F Freudiger

Jason Lee Douglas

Hon Yuk Chan

Steven J Falkenburg

Christopher S Linn

Keith Stattenfield

Guillaume Borios

Anubhav Malhotra

Mark Stemm

Stanley N Hung

Suma Desu

David Chi-Wei Yung

John M Hornkvist

Bryan Hansen

Ashwin Kashyap

Vivek Sehgal

Saravana Kumar Siva Kumaran

Thomas James Emerson

Karolina Buchner

Vojtech Jina

James A De Guerre

Rishab Alyer Ghosh

Charles Henry Salzenberg, Jr

Yogish Baliga

João Pedro De Almeida Forjaz De Lacerda

A method and apparatus of a device that performs a search using a deep link index is described. In an exemplary embodiment, the device receives a query on a device. The device additionally determines a plurality of results matching the query. The device further determines a subset of the plurality of results that correspond to at least one native application installed on the device. In addition, the device presents a link for each of the results in the subset of the plurality of results with data that launches the corresponding native application if that link is selected, where the link is a deep link that reference a location in the corresponding native application. Upon detecting one of the links corresponding to the subset of the plurality of results is selected, the device launches the corresponding native application with the data for that link.

Dynamic ranking function generation for a query

A method and apparatus of a device that re-rank a plurality of search results received from a search server on the device is described. In an exemplary embodiment, the device receives, with a browser of the device, a search query from a user. The device further sends the search query to a search server. In addition, the device receives the plurality of search results from the search server, wherein the plurality of search results is ranked according to a first ranking. The device also retrieves browser history of the user, wherein the browser history is collected on the device without revealing the browser history to the search server. The device further re-ranks the plurality of search results according to a second ranking based on at least the browser history. In addition, the device presents the plurality of search results using the second ranking.

Client-side search result re-ranking

A method and apparatus of a device that generates a re-ranking model used to re-rank a plurality of search results on a client device is described. In an exemplary embodiment, the device receives a crowd-sourced intra-domain model from a server, where the intra-domain model is a search result re-ranking model generated based on at least device interactions of a plurality of users interacting with a plurality of other devices. The device further generates a re-ranking model from the crowd-sourced intra-domain model and a local model, where the local model includes private data representing a device user's interaction with that device and the re-ranking model is used to re-rank a plurality of search results.

Blending learning models for search support

A new approach is proposed that contemplates systems and methods to ascribe or transfer metadata from one search-related entity to another, where each entity can be one of subject or source, citation, and object or target. First, one or more complete or incomplete attributes associated with one or more of entities across source, citation and target are identified with a high degree of probable accuracy, wherein such metadata or attributes include but are not limited to, time, language, and location of the entities. The identified attributes are then ascribed or transferred from one entity where the metadata is available to other search entities. Finally, the transferred attributes can be utilized to facilitate the selection and ranking of the cited targets for the search result.

System and method for metadata transfer among search entities

A method and apparatus of a device that performs a multi-domain query search is described. In an exemplary embodiment, the device receives a query prefix from a client of a user. The device further determines a plurality of search completions across the plurality of separate search domains. In addition, the device ranks the plurality of search completions based on a score calculated for each of the plurality of search completions determined by a corresponding search domain, where at least one of the plurality of search completions is used to generate a plurality of search results without an indication from the user and in response to receiving the query prefix.

Multi-domain query completion

A new approach is proposed that contemplates systems and methods to examine and determine quality of objects cited by citations in a search result based on a citation graph that includes citing subjects, citations, and cited objects. First, influence scores of a plurality of subjects/sources that compose the citations of the objects in the search result are calculated. The quality of the objects cited by the subjects can then be determined by examining the influence scores for the subjects of the citations. Finally, the cited objects selected can be presented to a user or provided to a thirty party for further processing together with the relevant citations and citing subjects.

System and method for determining quality of cited objects in search results based on the influence of citing subjects

A method and apparatus of a device that re-rank a plurality of search results is described. In an exemplary embodiment, the device receives a search query from a user and generates the plurality of search results over a plurality of search domains, wherein the plurality of search results is ranked according to a first ranking. The device additionally generates a re-ranking model, where the re-ranking model includes a plurality of intra-domain models that are generated based on at least based on-device interactions of a plurality of users interacting with a plurality of other devices and each of the plurality of search domains corresponds to one of the plurality of intra-domain models. The device further re-ranks the plurality of search results using the re-ranking model and presents the plurality of search results using the second ranking.

Re-ranking search results using blended learning models

Systems and methods are disclosed for suggesting expressive graphical content to a user to share within a messaging system. Expressive graphical content can include images, video, animated images, any of which may include sound, that a message system user is likely to share because it is related to a conversation between one or more users of the message system. Expressive graphical content may be content that is recent, humorous, and/or popular or trending in popularity, and can be shared without a copyright. A transcript of a message session between two or more users of a message system can be used to generate keywords for identifying and prioritizing expressive graphical content. The keywords can be prioritized and used as search terms to proactively suggest to the user to search for expressive graphical content. A search can be initiated automatically upon selecting one or more of the keywords.

Image search based on message history

A machine-readable medium that gathers a plurality of key terms is described. In an exemplary embodiment, the machine-readable medium receives a plurality of terms and selects a plurality of key terms from the plurality of terms, wherein each of the plurality of key terms is a term that is highlighted in a running application. The machine-readable medium further associates a predictive search query for each of the plurality of key terms, wherein the predictive search query is executed when that term is found in a running application and the user selects this term in the running application. The machine-readable medium additionally sends the plurality of key terms to a plurality of devices, wherein each of the plurality of devices matches at least one of the plurality of key terms in that device.

System and method of generating a key list from multiple search domains

A method and apparatus of a device that links a term in an application running on a device to a predictive search query is described. In one embodiment, the device receives a plurality of key terms from a key terms server, wherein each of the plurality of key terms is associated with the predictive search query. For each of the plurality of application terms, the device determines if there is a matching key term for this application term with at least one of the plurality of key terms. The device further receives an indication that a user has selected the matching key term. In addition, the device requests a query search to a search server using the predictive search query associated with the matching key term. Furthermore, the device receives a query search result from the query search server and presents the query search results to the user of the device.

System and method of highlighting terms

Indexing web pages with deep links

A method and apparatus of a device that performs a search using a plurality of application states is described. In an exemplary embodiment, the device receives a plurality of application states from a plurality of applications running on a device. The device further creates an index of the plurality of application states. In addition, the device receives a query to search for data stored on the device. Furthermore, the device searches the plurality of application states using the index and the query. The device additionally determines a match for the query of one of the plurality of the application states and returns the match for the matching application state.

In-application history search

A method and apparatus of a device that indexes an application state in a search query index. In this embodiment, receiving the application state of the application from another device coupled to the server. The device further generates a view of the application corresponding to the application state, wherein the view is a representation of a user interface of the application corresponding to the application state. In addition, the device indexes the view in a search query index.

Application view index and search

A method and apparatus of a device that ranks a plurality of query results from a plurality of search domains is described. In this embodiment, the device receives a query from a client. In addition, the device applies the query to the plurality of search domains and a broad-base search domain. Furthermore, the device receives the plurality of query results from the plurality of search domains and a set of broad-base query results from the broad-base search domain. The device additionally ranks the plurality of query results using the set of broad-base query results and returns a ranked plurality of query results to the client.

Federated search results scoring

Systems and methods are disclosed for generating term frequencies of known terms based on crowdsourced differentially private sketches of the known terms. An asset catalog can be updated with new frequency counts for known terms based on the crowdsourced differentially private sketches. Known terms can have a classification. A client device can maintain a privacy budget for each classification of known terms. Classifications can include emojis, deep links, locations, finance terms, and health terms, etc. A privacy budget ensures that a client does not transmit too much information to a term frequency server, thereby compromising the privacy of the client device.

Growing community of inventors

San Francisco, CA, United States of America

Vipul Ved Prakash