公开(公告)号：US20180219814A1

公开(公告)日：2018-08-02

申请号：US15421033

申请日：2017-01-31

Applicant: Yahoo! Inc.

Inventor： Yoelle Maarek ,  Ido Guy ,  Dan Pelleg ,  Idan Szpektor ,  Alexander Nus ,  Jeffrey Bonforte

IPC: H04L12/58 ,  G06F17/30 ,  G06T7/90 ,  G06K9/62 ,  G06K9/46

CPC classification number: H04L51/08 ,  G06F16/583 ,  G06K9/00677 ,  G06Q50/01 ,  H04L51/10

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosure provides a novel, computerized framework for automatically identifying and recommending socially-engaging photos to their creators for sharing. Execution of the disclosed systems and methods turns a tedious manual chore into an automated, software-driven process. The disclosed systems and methods utilizes a novel, computerized learn-to-rank (LTR) algorithm for identifying the most engaging, socially driven photos by: (a) grouping near-duplicate photos; (b) selecting a representative photo for sharing per group; and (c) ranking of the groups by their likelihood to contain a “shareable” photo.

公开(公告)号：US20180129732A1

公开(公告)日：2018-05-10

申请号：US15344869

申请日：2016-11-07

Applicant: Yahoo!, Inc.

Inventor： Dan Pelleg ,  Alexander Nus ,  Fiana Raiber ,  Ido Guy ,  Avihai Mejer

IPC: G06F17/30

CPC classification number: G06F16/3344 ,  G06F16/355 ,  G06F17/277 ,  G06N20/00

Abstract: One or more computing devices, systems, and/or methods for generating a set of tips for an entity are provided. For example, users may create user generated content describing an entity, such as a user review for a consumer good, a location, an event, etc. Because a user may be unable to read and digest all of the user reviews for the entity, the user may merely read a few user reviews, and thus miss out on useful information. Accordingly, tip templates, indicative of how tips are linguistically/grammatically constructed, are applied to the user reviews to automatically extract a set of tips for the entity (e.g., “make sure to bring a rain jacket”). The set of tips may be filtered to remove undesirable tips, ranked based upon usefulness, and/or diversified to remove redundant tips. In this way, a set of useful tips may be provided to the user.