Methods and systems are provided for associating Media Access Control (MAC) addresses with public chargers of electric vehicles, also known as Electric Vehicle Supply Equipment (EVSE), using a statistical approach and leveraging big data from connected vehicles (CV) and charge point operators (CPO). The data products generated by the method described herein can be utilized by electric vehicles (EV) to identify the charging EVSE during a public charging event.

Systems and methods are disclosed that include determining a user content feed for an individual user; transmitting the user content feed to the client device of the user for display of individual content items of the user content feed in succession; receiving a request to modify the queue of content items for the user content feed, wherein the request includes one or more contextual identifiers associated with a displayed content item; determining a modified user content feed for the individual user based on the one or more contextual identifiers associated with a displayed content item; and transmitting the modified user content feed to the client device of the user for display of individual content items of the user content feed in succession.

A text data structuring apparatus includes a processor, wherein the processor is configured to: extract text included in an image and position information of the text on the basis of Optical Character Recognition (OCR), extract line information included in the image by using the text, the position information, and the image, classify the text into text units by using natural language processing model, add a tag that combines a first tag and a second tag to each of the keywords included in each of the text units, connect keywords with related tags among the tagged keywords, label each of the connected keywords with key or value, acquire a mapping candidate group based on the line information on the basis of the line information, and decide which texts to be mapped to each other based on similarity scores between texts included in the mapping candidate group.

Conventionally, guardrails for artificial intelligence (AI) agents are static and rigid. As language usage evolves, these guardrails must be manually updated, which has become impractical as the number of AI agents has increased exponentially in recent years. Accordingly, disclosed embodiments provide automated semantic and context-aware expansion of agentic guardrails. In particular, base guardrails may be decomposed into base guardrail elements. The base guardrail elements may be semantically expanded into similar guardrail elements, for which context markers may be generated. New guardrails may be generated by combining these semantically similar guardrail elements with context markers, and these expanded guardrails may be incorporated into the AI agent.

Embodiments are directed towards previewing results generated from indexing data raw data before the corresponding index data is added to an index store. Raw data may be received from a preview data source. After an initial set of configuration information may be established, the preview data may be submitted to an index processing pipeline. A previewing application may generate preview results based on the preview index data and the configuration information. The preview results may enable previewing how the data is being processed by the indexing application. If the preview results are not acceptable, the configuration information may be modified. The preview application enables modification of the configuration information until the generated preview results may be acceptable. If the configuration information is acceptable, the preview data may be processed and indexed in one or more index stores.

A computer-implemented method may include (i) identifying graph data that includes a plurality of vertices connected by a plurality of edges, (ii) storing at least a portion of the graph data in a key-value store, (iii) receiving a query for the graph data, (iv) retrieving the graph data via the key-value store, and (v) returning the retrieved graph data in response to the query. Various other methods, systems, and computer-readable media are also disclosed.