The present disclosure provides methods and systems for quantifying item performance in a digital shelf. A method for quantifying item performance in a digital shelf may comprise: calculating a value associated with a shelf share of the given item; determining a set of factors for calculating a score indicative of the item performance on the digital shelf, wherein the set of factors includes the shelf share; generating, using a trained machine learning algorithm, the score based on the set of factors; and displaying the score within a graphical user interface (GUI) on an electronic device.

Certain embodiments of the present invention provide methods and systems for dynamic classification of electronic vendors. Certain embodiments provide a method for dynamic vendor classification. The method includes analyzing a vendor based on a comparison of vendor features; categorizing the vendor based on the analysis; and permitting access to the vendor according to the categorization of the vendor. The categorization may include trusted, not trusted, or unsure, for example. Analysis may include comparing a first outlet of the vendor with a second outlet of the vendor, for example. Analysis may include comparing an outlet of the vendor with an outlet of a second vendor, for example. A vendor may be defined as a particular outlet for a vendor and/or all outlets associated with a vendor (a vendor entity).

A method is described in which a topic similarity score, a product similarity score and an operating system similarity score between an original post and each one of a plurality of previous posts are determined; an overall similarity score of the each one of the plurality of previous posts based on the topic similarity score, the product similarity score and the operating system similarity score is determined; and a recommendation of a top K number of the plurality of previous posts based on the overall similarity score of the each one of the plurality of previous posts is sent to a display device.

A lodging reservation system is configured to receive lodging requests and display the lodging requests through a user interface. The system receives lodging offers in response to the lodging requests, and transmits the lodging offers to the originator of the lodging request. The system further is configured to receive a selection of a lodging offer from the transmitted lodging offers.

The disclosed apparatus, systems, and methods relate to a location query mechanism that can efficiently determine whether a target entity is located within a region of interest (ROI). At a high level, the location query mechanism can be configured to represent a ROI using one or more polygons. The location query mechanism can, in turn, divide (e.g., tessellate) the one or more polygons into sub-polygons. Subsequently, the location query mechanism can use the sub-polygons to build an index system that can efficiently determine whether a particular location is within any of the sub-polygons. Therefore, when a computing device queries whether a particular location is within the region of interest, the location query mechanism can use the index system to determine whether the particular location is within any of the sub-polygons.

According to various embodiments, an application recommendation device may be provided. The application recommendation device may include: a metrics determination circuit configured to determine a plurality of metrics; and a user input circuit configured to receive user input; a weight determination circuit configured to determine a plurality of weights based on the user input; a weighting circuit configured to determine a weighted metric based on weighting the plurality of metrics based on the plurality of weights; and a recommendation determination circuit configured to determine a recommended application based on the weighted metric.

A multimodal recommendation identification system analyzes data describing a sequence of past content item interactions to generate a recommendation for a content item for a user. An indication of the recommended content item is provided to a website hosting system or recommendation system so that the recommended content item is displayed or otherwise presented to the user. The multimodal recommendation identification system identifies a content item to recommend to the user by generating an encoding that encodes identifiers of the sequence of content items the user has interacted with and generating encodings that encode multimodal information for content items in the sequence of content items the user has interacted with. An aggregated information encoding for a user based on these encodings and a system analyzes the content item sequence encoding and interaction between the content item sequence encoding and the multiple modality encodings to generate the aggregated information encoding.

A multimodal recommendation identification system analyzes data describing a sequence of past content item interactions to generate a recommendation for a content item for a user. An indication of the recommended content item is provided to a website hosting system or recommendation system so that the recommended content item is displayed or otherwise presented to the user. The multimodal recommendation identification system identifies a content item to recommend to the user by generating an encoding that encodes identifiers of the sequence of content items the user has interacted with and generating encodings that encode multimodal information for content items in the sequence of content items the user has interacted with. An aggregated information encoding for a user based on these encodings and a system analyzes the content item sequence encoding and interaction between the content item sequence encoding and the multiple modality encodings to generate the aggregated information encoding.

The present disclosure provides an event information push method performed at a computer system, the method including: collecting network messages from a social networking platform; performing aggregation on the network messages, to obtain corresponding event information; obtaining, for each piece of event information, one or more attributes from the corresponding category of network messages; obtaining, from an event information and user database, a user group corresponding to the one or more attributes of each piece of event information; and pushing each piece of event information to a user in the user group corresponding to the event information.

The disclosed technologies can compute inferred taste preferences relating to food products and food providers using objectively verifiable data, including order data, and use these inferred taste preferences to create new functionality in an information search and retrieval system and/or a product ordering system.