Abstract: A system and method to identify a document including text relating to a merchant system. The document is segmented into a set of sentences. A first machine-learning model executed by a processing device generates an initial topic segmentation corresponding to the set of sentences. A second machine-learning model is applied to the initial topic segmentation to generate a final topic segmentation corresponding to the document.

Abstract: A system and method to receive a search query input from an end user system, wherein the search query input relates to information associated with a merchant system. In view of the search query, a document associated with the merchant system is identified. A set of portions of the document are identified. A keyword-matching density level is determined for each portion of the set of portions of the document. A selected portion of the set of portions having a highest relative keyword-matching density level is identified. A graphical user interface including a search result responsive to the search query is generated, the graphical user interface including the selected portion of the document.

Abstract: A system and method to receive a search query input from an end user system, wherein the search query input relates to information associated with a merchant system. In view of the search query, a document associated with the merchant system is identified. A set of portions of the document are identified. A keyword-matching density level is determined for each portion of the set of portions of the document. A selected portion of the set of portions having a highest relative keyword-matching density level is identified. A graphical user interface including a search result responsive to the search query is generated, the graphical user interface including the selected portion of the document.

Abstract: A system and method to generate search results in response to a search query based on comparisons of embedding vectors. The system and method receive, from an end user system, a search query including a set of keywords associated with the entity. Using a neural network, an embedding vector is identified based on the set of keywords of the search query. The system and method compares the embedding vector associated with the search query to a set of embedding vectors associated with a set of structured data elements relating to the entity. Based on the comparison, a set of matching structured data elements is identified. The system and method generate a search result in response to the search query, wherein the search result includes at least a portion of the set of matching structured data elements. The search result is displayed via an interface of the end user system.

Abstract: A system and method to generate search results in response to a search query based on comparisons of embedding vectors. The system and method receive, from an end user system, a search query including a set of keywords associated with the entity. Using a neural network, an embedding vector is identified based on the set of keywords of the search query. The system and method compares the embedding vector associated with the search query to a set of embedding vectors associated with a set of structured data elements relating to the entity. Based on the comparison, a set of matching structured data elements is identified. The system and method generate a search result in response to the search query, wherein the search result includes at least a portion of the set of matching structured data elements. The search result is displayed via an interface of the end user system.

Abstract: A system and method to receive a search query including a set of search terms associated with a merchant system. A machine-learning model is executed to identify a first subset of one or more multi-term phrases associated with one or more named entity types. A set of tokens corresponding to the search query is generated, wherein the set of tokens comprises a token associated with each of the first subset of one or more multi-term phrases. A comparison of the set of tokens to a document index associated with the merchant system is executed to identify one or more matching documents. Based on the comparison, a set of search results comprising the one or more matching documents is generated.

Abstract: A system and method to generate and manage clusters of search terms. A cluster generation process is executed at a first time to generate a first set of clusters including respective sets of search terms. At least one of a first value of a first parameter associated with the first set of clusters or a first value of a second parameter associated with the first set of clusters is determined. At a second time, the cluster generation process is executed to generate a second set of clusters. At least one of a second value of the first parameter associated with the second set of clusters or a second value of the second parameter associated with the second set of clusters is determined. A determination is made whether either the second value of the first parameter satisfies a first condition or the second value of the second parameter satisfies a second condition.

Abstract: A system and method to generate and manage clusters of search terms. The system and method generate a cluster including a set of search terms. A size of the cluster is compared to a cluster size threshold level to determine that the cluster comprises a valid-sized cluster. A noise rate of the cluster is compared to a noise rate threshold level to determine that the noise rate is less than the noise rate threshold level, wherein the noise rate relates to a distance of the cluster from a set of other clusters. Performance data associated with the cluster is generated based on a comparison with one or more cluster performance metric thresholds. A user interface is generated to display information associated with the cluster comprising the performance data. Input is received via the user interface comprising an adjustment of the one or more cluster performance metrics thresholds.

Abstract: Systems, methods, and computer-readable storage media for receiving data at a computer system, wherein the data has a plurality of rows; receiving, from a user at the computer system, a description of a task associated with the data; receiving, from the user at the computer system, a plurality of example transformations; combining, via at least one processor of the computer system, the task description together with the plurality of example transformations and input and output labels, resulting in a prompt; executing, via the at least one processor, a machine learning model, wherein the prompt is an input to the machine learning model, and wherein output of the machine learning model comprises an algorithm for executing the task; and executing, via the at least one processor, the task on the data using the algorithm.

Abstract: A merchant listing verification system to scan a publisher system of a set of publisher systems to identify a published merchant listing published by the publisher system, where the published merchant listing includes a first set of data fields and a first set of data field values associated with a merchant system. The merchant listing verification system compares, on a field-by-field basis, the published merchant system to a target merchant listing comprising a second set of data fields and a second set of data field values associated with the merchant system. Based on the comparing, a discrepancy between a first data value of a first data field of the first set of data fields of the published merchant listing and a second data value of a second data field of the second set of data fields of the target merchant listing is identified.

Abstract: A system and method to generate and manage clusters of search terms. The system and method collect a set of search terms associated with multiple search queries relating to an entity. A neural network identifies a set of embedding vectors, wherein each of the set of embedding vectors represents a search term of the set of search terms. A cluster is generated including a portion of the set of search terms based on a comparison of embedding vectors associated with the portion of the set of search terms. A size of the cluster is compared to a cluster size threshold level to determine if a first condition is satisfied. In response to determining satisfaction of the first condition, the cluster is identified as a valid-sized cluster. A user interface is generated to display information related to the cluster and one or more cluster metrics.

Abstract: A system and method to receive a search query input from an end user system, wherein the search query input relates to information associated with a merchant system. In view of the search query, a document associated with the merchant system is identified. A set of portions of the document are identified. A keyword-matching density level is determined for each portion of the set of portions of the document. A selected portion of the set of portions having a highest relative keyword-matching density level is identified. A graphical user interface including a search result responsive to the search query is generated, the graphical user interface including the selected portion of the document.

Abstract: A system and method to generate and manage clusters of search terms. A cluster generation process is executed at a first time to generate a first set of clusters including respective sets of search terms. At least one of a first value of a first parameter associated with the first set of clusters or a first value of a second parameter associated with the first set of clusters is determined. At a second time, the cluster generation process is executed to generate a second set of clusters. At least one of a second value of the first parameter associated with the second set of clusters or a second value of the second parameter associated with the second set of clusters is determined. A determination is made whether either the second value of the first parameter satisfies a first condition or the second value of the second parameter satisfies a second condition.

Abstract: A system and method to generate and manage clusters of search terms. The system and method collect a set of search terms associated with multiple search queries relating to an entity. A neural network identifies a set of embedding vectors, wherein each of the set of embedding vectors represents a search term of the set of search terms. A cluster is generated including a portion of the set of search terms based on a comparison of embedding vectors associated with the portion of the set of search terms. A size of the cluster is compared to a cluster size threshold level to determine if a first condition is satisfied. In response to determining satisfaction of the first condition, the cluster is identified as a valid-sized cluster. A user interface is generated to display information related to the cluster and one or more cluster metrics.

Abstract: A system and method to generate search results in response to a search query based on comparisons of embedding vectors. The system and method receive, from an end user system, a search query including a set of keywords associated with the entity. Using a neural network, an embedding vector is identified based on the set of keywords of the search query. The system and method compares the embedding vector associated with the search query to a set of embedding vectors associated with a set of structured data elements relating to the entity. Based on the comparison, a set of matching structured data elements is identified. The system and method generate a search result in response to the search query, wherein the search result includes at least a portion of the set of matching structured data elements. The search result is displayed via an interface of the end user system.

Abstract: A technique includes introducing an electrical perturbation to a fuel cell system during operation of the fuel cell system. This electrical perturbation does not substantially disrupt the operation of the fuel cell system. In response to the perturbation, an electrical parameter of the fuel cell system is measured.

Abstract: A technique includes introducing an electrical perturbation to a fuel cell system during operation of the fuel cell system. This electrical perturbation does not substantially disrupt the operation of the fuel cell system. In response to the perturbation, an electrical parameter of the fuel cell system is measured.