Oath Inc.

Disclosed are embodiments for generating a dataset metadata file based on partial metadata files. In one embodiment, a method is disclosed comprising receiving data to write to disk, the data comprising a subset of a dataset; writing a first portion of the data to disk; detecting a split boundary after writing the first portion; recording metadata describing the split boundary; continuing to write a remaining portion of the data to disk; and after completing the writing of the data to disk: generating a partial metadata file for the data, the partial metadata file including the split boundary, and transmitting the partial metadata to a partial metadata collector.

Disclosed are embodiments for replacing database table join keys with index keys. In one embodiment, a method is disclosed comprising: receiving, by a processor, annotation data, the annotation data comprising a set of rows; retrieving, by the processor, a root dataset, the root dataset stored in one or more files; generating, by the processor, a row identifier for each row in the set of rows, the row identifier storing a plurality of fields enabling alignment of a respective row in the annotation data to a corresponding row in the root dataset; generating, by the processor, an annotation dataset, the annotation dataset comprising the set of rows and corresponding row identifiers; and writing, by the processor, the annotation dataset to at least one file, the at least one file separate from the one or more files.

Disclosed are embodiments for sorting rows of a dataset after a JOIN operation. In one embodiment, a method is disclosed comprising performing a JOIN operation on an annotation dataset, the performing of the JOIN operation generating an unordered dataset; grouping a plurality of rows in the unordered dataset into a plurality of buckets, the grouping performed based on a root dataset associated with the annotation dataset; sorting each bucket, the sorting comprising sorting each bucket independently; and combining each sorted bucket into a sorted dataset.

The present teaching relates to a method, system, and programming for content personalization. A request is received from a user to obtain a content item. Information indicative of a literacy-level of the user is obtained and the content item to be provided to the user is retrieved. The content item is modified by updating information included in the content item based on the literacy-level of the user to generate an updated content item. The updated content item is provided to the user in response to the request.

One or more computing devices, systems, and/or methods for content item selection for goal achievement are provided herein. A goal of a user is identified. A model is utilized to evaluate the goal, user information, and a set of content items to generate predictions for the content items of how likely each content item will be a causation factor of the user making progress towards the goal in response to the user being provided with each content item. A target content item is selected from the set of content items based upon the target content item having a predicted likelihood of being the causation factor above a threshold. The target content item is provided through a registered media channel accessible through a device of the user.

The present teaching relates to personalized content recommendation. A webpage is contrasted for a user having a plurality of slots each of which is to be allocated with a content item. For each of the plurality of slots, a plurality of content items in a plurality of types of content are accessed. For each of the plurality of types of content, a personalized score is predicted for each content item in the type of content, wherein the personalized score is obtained based on a trained model trained. A recommended content item of the type of content is selected based on personalized scores. An overall recommended content item is selected and allocated to a slot based on criteria associated with the personalized scores of the recommended content items and a business rule. The webpage with the plurality of slots allocated with content items is provided to the user.

One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A request for content may be received. A second plurality of content items associated with a plurality of rankings may be selected from a plurality of content items based upon a plurality of bid values. A quantity of content items of the second plurality of content items may be greater than a quantity of content items associated with the request for content. One or more ghost content items associated with one or more rankings of the plurality of rankings may be identified. A ghost impression indicator associated with a ghost content item of the one or more ghost content items may be stored based upon a determination that a ranking, of the one or more rankings, associated with the ghost content item matches a second ranking of a presented content item.

One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.

One or more computing devices, systems, and/or methods are provided. One or more first signals received from one or more first devices may be monitored. One or more first threat indicators within a first signal of the one or more first signals may be detected. One or more second signals may be analyzed to determine a probability of a threat event. One or more second devices of a plurality of devices may be selected, based upon the probability, for transmission of one or more messages associated with the threat event.

The present teaching relates to a method, system, and programming for searching content. A sketch of an object is obtained from a user. The sketch is processed by a neural network to generate an image corresponding to the sketch of the object. One or more features are extracted from the image, and one or more images previously stored are identified that have features similar to the one or more features. The one or more images are provided to the user.