Abstract: The present disclosure discloses a system and method for batch and real-time feature computation, and the system includes: a management server, one or more batch feature computing units, one or more distributed computing units, one or more real-time feature computing units, an offline database and a real-time database. The management server receives a script containing feature computing logics, starts batch feature computation in a batch feature computing scenario, and deploys the script in a real-time feature computing scenario to generate a real-time computing plan, wherein the script containing the feature computing logics has unity for batch feature computing logics and real-time feature computing logics, and the real-time database obtains and stores data for the real-time feature computation from the offline database. According to the present disclosure, the batch feature computing logics and the real-time feature computing logics may be unified by the script.

Abstract: Techniques for modifying queries in a set of nested queries are disclosed. A graphical user interface displays a query detail region alongside a nested query display region. The graphical user interface includes functionality to provide for modification of queries in the nested set of queries. Based on a selection by a user, a query modification tool promotes a query attribute from a child query to one or more parent queries. Based on another selection by a user associated with one query in the set of nested queries, the system deletes an attribute from each query in the set of nested queries. Responsive to a selection to create multiple conditions for a query rule, the system modifies the functionality of the user interface to enable entry of multiple condition characteristics. Based on a further selection, the system creates the multiple conditions for the query rule.

Abstract: An interactive search session is implemented using an artificial intelligence model. For example, when the artificial intelligence model receives a search query from a user, the model selects an action from a plurality of actions based on the search query. The selected action queries the user for more contextual cues about the search query (e.g., may enquire about use of the search results, may request to refine the search query, or otherwise engage the user in conversation to better understand the intent of the search). The interactive search session may be in the form, for example, of a chat session between the user and the system, and the chat session may be displayed along with the search results (e.g., in a separate section of display). The interactive search session may enable the system to better understand the user's search needs, and accordingly may help provide more focused search results.

Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.

Abstract: Methods, systems, and computer program products for active learning for natural language question answering are provided herein. A computer-implemented method includes generating a semantic signature of a natural language query; generating a SQL signature for a SQL query corresponding to the natural language query; determining whether a set of mappings includes a semantic signature matching the generated semantic signature, wherein each mapping in the set is between (i) a given semantic signature and (ii) a SQL signature representing a class of SQL queries corresponding to the given semantic signature; and in response to determining that the set of mappings does not include the generated semantic signature, adding a mapping between the generated semantic signature and the generated SQL signature to the set of mappings.

Abstract: An embodiment for identifying and replacing logically neutral phrases in natural language queries may include receiving a natural language query. The embodiment may also identify one or more logically neutral or non-logically neutral anchors in the natural language query. The embodiment may also identify boundaries containing one or more logically neutral phrases. The embodiment may further include detecting semantic and logical relations between verbal phrases and functional language between and adjacent to the one or more logically neutral and non-logically neutral anchors to reintroduce non-logically neutral language back into a non-logically neutral portion of the natural language query. The embodiment may also include generating a modified natural language query by automatically removing the boundaries and optionally replacing the one or more logically neutral phrases in the natural language query.

Abstract: The subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation and at least one join operation. The subject technology analyzes the query plan to identify an aggregation that is redundant. The subject technology removes the aggregation based at least in part on the analyzing. The subject technology determines at least one aggregation property corresponding to at least one query operation of the query plan. The subject technology inserts at least one adaptive aggregation operator in the query plan based at least in part on the at least one aggregation property, the at least one aggregation property comprising a set of aggregation properties. The subject technology provides a modified query plan based at least in part on the inserted at least one adaptive aggregation operator in the query plan.

Abstract: A method for intelligent query plan cache size management can be implemented. During execution of a plurality of incoming queries in a database management system, the method can measure actual compilation times of generating query execution plans for the plurality of incoming queries. The database management system can have a query execution plan cache which has a size that can store at least some of the query execution plans. The method can monitor differences between the actual compilation times and ideal compilation times of generating query execution plans for the plurality of incoming queries. The ideal compilation times can be estimated by assuming no query execution plan is evicted from the query execution plan cache. The method can adjust the size of the query execution plan cache based on the monitored differences.

Abstract: A large highly parallel database management system includes thousands of nodes storing huge volume of data. The database management system includes multiple query optimizers for determining low cost execution plans for queries. The database management system is adapted to receive a data query. An execution plan generator component of the database management system generates an initial execution plan for the query. The initial execution plan is fed as input to more than one query optimizers. Each optimizer starts with the initial execution plan, generates alternative execution plans, and determines a satisfactory execution plan that incurs the lowest cost. The database management system compares the selected execution plans by the optimizers and selects one with the lowest cost. The multiple query optimizers run in parallel.

Abstract: Systems and methods for reducing usage of computational resources when accessing siloed data across disparate locations via a unified metadata graph are disclosed. The system receives a user-specified query indicating a request to access a set of data objects. The system then performs natural language processing on the user-specified query to determine a set of phrases corresponding to the user-specified query. The system then accesses a metadata graph to determine a node corresponding to the set of phrases. Using a location identifier corresponding to the determined node, the system determines a data silo storing at least one data object of the set of data objects. The system then generates for display, on a graphical user interface, a visual representation of the at least one data object.

Abstract: A method for stratified-sampling-based query execution includes: receiving a query; collecting a first data sample from the first dataset using a non-stratified sampling technique; performing statistical analysis on the first data sample; identifying a stratum classifier from the statistical analysis; generating a stratum classification by calculating strata boundaries for the stratum classifier; and calculating a result to the query based on analysis of the second data sample.

Abstract: Systems and methods are disclosed to implement a bounded group by query system that computes approximate time-sliced statistics for groups of records in a dataset according to a group by query. In embodiments, a single pass scan of the dataset is performed to accumulate exact results for a maximum number of groups in a result grouping structure (RGS) and approximate results for additional groups in an approximate result grouping structure (ARGS). RGSs and ARGSs are accumulated by a set of accumulator nodes and provided to an aggregator node, which combines the received structures to generate exact or approximate statistical results for at least a subset of the groups in the dataset. Advantageously, the disclosed query system is able to produce approximate results for at least some of the groups in a single pass of the dataset using size-bounded data structures, without predetermining the actual number of groups in the dataset.

Abstract: A continuous query identified by an archived relation of an application may be received. A physical query plan may be generated for the continuous query and/or a child operator plan may be identified. A buffer operator may be inserted between the child operator and its parent operator and/or the event information from the child operator may be stored in the buffer operator. A query operator may be identified in the physical query plan. It may be determined that the query operator identified in the physical query plan is a same type as a second query operator in a second continuous query concurrently executing. Further, a combined query plan may be generated based at least in part on the query operator identified in the physical query plan being the same type as the second query operator in the second continuous query.

Abstract: A determination is made as to whether a data type associated with a received logical table definition associated with a database query within a distributed database system differs from a data type associated with a local logical table definition. A data conversion is performed on data retrieved from a locally-stored physical table referenced by the local logical table definition in response to determining that the data types differ. Local data conversion information is created identifying the data conversion performed on the retrieved data in response to performing the data conversion. At least one of the retrieved data and the converted data with the created local data conversion information is forwarded to at least one of a distributed database node and an application-level module.

Abstract: A computing system for querying multiple data sources and a method therefor is provided. The computing system may comprise one or more nodes in communication with at least one data source of the multiple data sources to access data therefrom. The computing system may further comprise a second node in communication with the one or more nodes. The second node may be configured to receive a query instance and process the query instance to generate one or more relational query instances. The one or more relational query instances may be distributed among the one or more nodes to extract data from the at least one data source in communication therewith corresponding to the respective one or more relational query instances. The second node may be further configured to receive extracted data from each of the one or more nodes queried. The second node may be further configured to aggregate the extracted data.

Abstract: A computer-implemented method for generating results for a client-requested query involves receiving a query produced by a client communication device, generating a result for the query in response to reception of the query, determining one or more predictive follow-up requests before receiving an actual follow-up request from the client device, and initiating retrieval of information associated with the one or more predictive follow-up requests, and transmitting at least part of the result to the client device, and then transmitting to the client device at least part of the information associated with the one or more predictive follow-up requests.

Abstract: Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. Machine learning-based classification can be performed to classify logs. This approach is used to group logs automatically using a machine learning infrastructure.

Abstract: In an embodiment, a plurality of ballots (1) for a plurality of candidates, (2) generated by a plurality of search engines, and (3) for a job description are received. Each ballot from the plurality of ballots is generated by a search engine from the plurality of search engines different than remaining search engines from the plurality of search engines. A mathematical representation that indicates, for each candidate from the plurality of candidates, how many other candidates from the plurality of candidates that candidate was ranked higher than in the plurality of ballots is generated. A final ballot ranking the plurality of candidates is generated using a trained statistical model and based on the mathematical representation. A candidate from the plurality of candidates for the job description is identified based on the final ballot.

Abstract: A system for data processing using machine learning processing and distributed architecture is described. Specifically, proprietary data transformation rules to be applied for the data processing may be stored at edge computing devices, while the bulk of data processing may be performed at a central computing node that houses the databases. A subset of a data set, in the database, may be sent from the central computing node to the edge computing node. The edge computing node may generate a second data set based on applying data transformation rules to the subset of the data set. The central computing node may determine, using a machine learning (ML) algorithm and based on the subset of the data set and the second data set, the data transformation rules, which may then be applied to the rest of the data set.

Abstract: The present disclosure provides systems for encoding transforms based on intent to be useable by developers. The system receives input datasets, generates output datasets, and identifies characteristics of the input or output datasets. Using these characteristics, the system can encode transforms associated with the datasets based on intent. The system stores and/or associates the intent-encoded transforms in data profiles, so that the system enables the transforms to be searched, recommended, and/or combined.

Abstract: Systems and methods are provided for management of data access latency in a distributed storage system by dynamically replicating data objects experiencing a high request volume. When a storage node is unable to meet a data access latency target (e.g., due to one or more data objects hosted by the storage node being the subject of a large quantity of requests), the storage node may initiate a process by which a second storage node is employed to reduce the request processing load. The second storage node may cache a copy of the requested data object, and may service at least a portion of requests for the data object using the cached copy.

Abstract: Certain aspects of the present disclosure provide techniques for bridging transactions across blockchains. The method generally includes receiving a request to invoke an atomic transaction including operations performed on a first blockchain and operations performed on a second blockchain. Generally, the atomic transaction is completed when an enumerated set of operations are completed. A first operation in the enumerated set of operations is initiated on the first blockchain. Initiating the first operation on the first blockchain triggers initiation of one or more second operations on the second blockchain. Completion of the one or more second operations for the atomic transaction is detected on the second blockchain, indicating that the operations of the atomic transaction relevant to the second blockchain have been completed on the second blockchain. Based on detecting completion of the one or more second operations on the second blockchain, the atomic transaction is finalized on the first blockchain.

Abstract: Disclosed herein are devices and methods for the selective tracing of Cannabis containing vaporizer cartridge through their lifecycle. A permanently a radio frequency identifier (RFID) that is near field communication (NFC) compatible is associated with a vaporizer cartridge having an assigned a unique identifier tag (UIT) and, utilizing a blockchain platform to allow each node in the supply and distribution chain to ledger and in their block of data to the NFC RFID of their transaction.

Abstract: A synchronization system node may comprise one or more processors and a synchronization database. The synchronization database may comprise a subscriber list of a plurality of subscribers, a first buffer including a plurality of attributes in a first state, and a second buffer including the plurality of attributes in a second state. The node may be configured to receive updates for one or more of the plurality of attributes and store, to the first buffer, the updates for the one or more of the plurality of attributes to update the plurality of attributes of the first buffer to an updated first state. While receiving the updates from the publisher, the nod may publish, from the second buffer to a first subscriber of the plurality of subscribers, one or more of the plurality of attributes in the second state.

Abstract: A clustering device includes a storage means configured to store a transposed file including array elements in a storage unit, the array elements storing a pair in which a cluster identifier and a first non-zero feature quantity of a mean feature vector are associated with each feature identifier, a calculation means configured to calculate a distance between the object feature vector in sparse representation indicating the object feature vector in a pair in which a second non-zero feature quantity of the object feature vector and a feature identifier of the second non-zero feature quantity are associated with each other, and the mean feature vector of each cluster, and an assignment means configured to assign the object feature vector to one of the plurality of clusters on the basis of the distance, and the calculation means calculates a product of a second non-zero feature quantity and a first non-zero feature quantity stored in an array element of an index based on a feature identifier corresponding to the

Abstract: A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues with the plurality of components. The data is analyzed and categorized based at least in part on the analysis. In the method, one or more application programming interfaces (APIs) are selected to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the categorization of the data, and the data is pushed to the one or more APIs.

Abstract: A method and system for determining anomalies in call center communications. Data relating to communications is streamed and processed to obtain baseline probability distributions over various domains of communications. Streams related to subsequent calls are compared to the baselines to determine anomalies.

Abstract: A data processing system that receives user input specifying datasets on which operations are performed with user interfaces that enable manipulation of hierarchical groups of datasets. A user interface may enable individual datasets or a previously defined group of datasets to be aggregated into another grouping. The groupings may be scoped, including by persona of users, such that, when a user is prompted to specify one or more datasets as a target of an operation by the data processing system, the available choices are limited to datasets that have a scope encompassing that user. The interfaces may prompt a user to select a grouping within the hierarchy that contains datasets on which the operation can be performed. Upon selection of a grouping with multiple datasets as a target of an operation that is performed on datasets singly, the operation may be performed on each dataset in the selected group.

Abstract: Methods and systems for gathering information from a user include identifying an origin topic and a target topic. A path from the origin topic to the target topic is determined. The path includes a set of bridging topics, where each bridging topic in the path is within a threshold distance in a semantic space from a previous topic and a subsequent topic. An interactive conversation is conducted with the user, introducing each topic in the path until the target topic has been reached. At least one predetermined piece of information relating to a user response to the target topic is recorded.

Abstract: Systems and methods for generating customized annotations of a medical record are provided. The system receives a medical record and processes it using a predictive model to identify evidence of a finding. The system then determines whether to have a recall enhancement or validation of a specific finding. Recall enhancement is used to tune or develop the predictive model, while validation is used to rapidly validate the evidence. The source document is provided to the user and feedback is requested. When asking for validation, the system also highlights the evidence already identified and requests the user to indicate if the evidence is valid for a particular finding. If recall enhancement is utilized, the source document is provided and the user is asked to find evidence in the document for a particular finding. The user may then highlight the evidence that supports the finding. The user may also annotate the evidence using free form text.

Abstract: At least some embodiments are directed to a system to compute uniform structured summarization of customer chats. In at least some embodiments, the system may operate a processor and receive a corpus of chats between customers and customer service representatives of an enterprise. Grouping the corpus of chats into subgroup task types and then extracting chat keywords and chat related words for each subgroup task type. Generating an expandable template data structure for each subgroup task type. Processing at least one chat to extract chat utterances and chat snippets ranking the chat utterances and chat snippets. Populating the expandable template data structure based on rankings to generate a chat summary data structure.

Abstract: Programs, systems, and methods for generating a support tree for automated resolution of user issues. In some embodiments, historical data may be obtained from a history of support interactions including historical issues and solutions to the historical issues. Most used solutions may be determined and stored with associated historical issues. Clusters of issues and solutions may be generated and labeled for generation of support tree nodes. Furthermore, solutions may be correlate such that a plurality of solutions may be provided for the resolving user issues. In some embodiments, issue data indicative of user issues may be provided by users. As the user provides issue data, deflections between nodes on the support tree may narrow a field of potential solutions to one or more solutions to be provided to the user.

Abstract: An artificial intelligence (AI) method includes a processor receiving, from a human user, a query on an external database; performing transformations on the query to produce a refined query; generating an embedding of the refined query; and generating a system prompt and a user prompt based on the refined query. The processor then applies the embedding to a vector database by executing a similarity routine to identify discrete vectors in the vector database most similar to the embedding, and collects the most similar vectors for application to a large language model. Next, the processor applies the most similar vectors, the refined query, and the system and user prompts to a large language model to generate a comprehensive response to the query. The response includes a text document that is generated by execution of the large language model.

Abstract: The present disclosure is directed to enabling acquisition of information of an argument corresponding to a case. The present disclosure is a language processing apparatus which refers to an argument emergence history database 14 which stores argument emergence patterns associated with cases and arguments of verbs for each meaning of a word or usage of a verb, acquires an argument emergence pattern which matches a verb and a case of the verb included in a request from a user from the argument emergence history database 14, and generates a response to the user using an argument included in the argument emergence pattern acquired from the argument emergence history database 14.

Abstract: A system and method for table conversion including converting a table containing text in tabular form to an image, labeling each text area of the image with a bounding box, determining for each bounding box, a position information, a semantic information, and an image information, reconstructing the image into a graph form having a plurality of nodes, wherein each node represents the bounding box of the text areas of the image, inputting at least two nodes into a trained neural network to determine a relative relationship between the at least two nodes, building a knowledge graph using the relative relationship of the at least two nodes, and translating the knowledge graph into machine readable natural language.

Abstract: Presented herein are techniques for a non-intruding auto quoting feature on-the-fly for chat applications based on previous conversations and effectively forking/quoting such conversations to ease the burden of the user going through all the chat history. The techniques may involve monitoring an ongoing first text communication session between a first user and at least one second user; detecting one or more salient words or phrases in the first text communication session based on the monitoring; based on the one or more salient words or phrases, identifying a second text communication session that is topically related to the first text communication session; and displaying in a user interface presented to the first user a prompt to quote relevant content from the second text communication session into the first text communication session or to fork the first user to be a participant in the second text communication session.

Abstract: A calculation unit (15a) calculates a degree of association between words included in compound word candidates that are each constituted by consecutive words in a document. The calculation unit (15a) calculates the degree of association by using a conditional probability that is a probability of a word that precedes a last word being present in the document under the condition that the last word follows. A selection unit (15b) selects, as a compound word, a compound word candidate whose degree of association thus calculated is higher than a predetermined threshold value. A learning unit (15c) learns a positional relationship between words that include the selected compound word in the document and predetermined tags added to the document. An addition unit (15d) adds the predetermined tags to the document based on the positional relationship between words that include the learned compound word in the document and the predetermined tags added to the document.

Abstract: A media segment of audio or video content can be identified by deriving data from media content and comparing the data to a reference database to identify the video segment. The speed and accuracy of the media identification process can be improved by advantageously partitioning the indexes in subdivisions where high value reference information is separated from the bulk information.

Abstract: Disclosed is a method for determining a content associated with a voice signal, which is performed by a computing device. The method may include converting a voice signal and generating text information. The method may include determining a plurality of target word candidates. The method may include determining a target word among the plurality of target word candidates based on a comparison between the plurality of target word candidates and the generated text information. The method may also include determining a content associated with the target word.

Abstract: Implementations disclose comprehensibility-based identification of educational content of multiple content types. A method includes determining respective comprehensibility ranking signals for content items corresponding to a user request, the comprehensibility ranking signals based on learning attribute scores generated for the content items from at least one machine learning model, determining a learning level of a user corresponding to the user request, ranking the content items based on a mapping between the learning level and the respective comprehensibility ranking signals of the content items, and providing a recommendation for the content items according to the ranking of the content items.

Abstract: Disclosed examples determine a unique audience exposed to media while reducing memory resources of a computing device. Example instructions program programmable circuitry to log a plurality of impressions corresponding to media accessed at client devices; generate a first value based on a count of the impressions and a count of users of a database proprietor that accessed the media; generate a second value based on the first value and a count of demographic impressions logged by the database proprietor; and determine a unique audience size based on the second value.

Abstract: The present disclosure describes a system and method of developing a search database for automated content curation. The processing arrangement is configured to store a plurality of slides related to one or more fields in the database arrangement, generate a plurality of thumbnails from the stored plurality of slides, extract a plurality of metadata from the plurality of thumbnails, wherein the plurality of metadata are extracted by processing the generated plurality of thumbnails through an optical character reader, store the extracted plurality of metadata into the search database, create an index comprising of associations between the plurality of slides, the plurality of associated metadata and the generated plurality of thumbnails, store the created index in the search database and curate content from the index of the search database based on the one or more search strings.

Abstract: A processor-implemented liveness test method includes detecting a face region in a query image, the query image including a test object for a liveness test, determining a liveness test condition to be applied to the test object among at least one liveness test condition for at least one registered user registered in a registration database, determining at least one test region in the query image based on the detected face region and the determined liveness test condition, obtaining feature data of the test object from image data of the determined at least one test region using a neural network-based feature extractor, and determining a result of the liveness test based on the obtained feature data and registered feature data registered in the registration database and corresponding to the determined liveness test condition.

Abstract: Implementations are described herein for leveraging digital media files retrieved and/or created by users to predict/determine topics of potential relevance to the users. In various implementations, digital media file(s) created and/or retrieved by a user with a client device may be applied as input across trained machine learning model(s), which in some cases are local to the client device, to generate output that indicates object(s) detected in the digital media file(s). Data indicative of the indicated object(s) may be provided to a remote computing system without providing the digital media file(s) themselves. In some implementations, information associated with the indicated object(s) may be retrieved and proactively output to the user. In some implementations, a frequency at which objects occur across a corpus of digital media files may be considered when determining a likelihood that a detected object is potentially relevant to a user.

Abstract: Disclosed computer-based systems and methods for analyzing a plurality of audio files corresponding to text-based news stories and received from a plurality of audio file creators are configured to (i) compare quality and/or accuracy metrics of individual audio files against corresponding quality and/or accuracy thresholds, and (ii) based on the comparison: (a) accept audio files meeting the quality and/or accuracy thresholds for distribution to a plurality of subscribers for playback, (b) reject audio files failing to meet one or more certain quality and/or accuracy thresholds, (c) remediate audio files failing to meet certain quality thresholds, and (d) designate for human review, audio files failing to meet one or more certain quality and/or accuracy thresholds by a predetermined margin.

Abstract: A computer-implemented method for contextually applying audio to an electronic media content, includes the following steps: parsing the electronic media content to determine at least one context of the electronic media content; comparing the at least one context of the electronic media content against a database of context tags corresponding to at least one context of a plurality of audio files; generating a ranked list of audio files corresponding to the comparison of the at least one context of the electronic media content against the database of context tags; selecting at least one audio file from the ranked list; and outputting the electronic media file together with the at least one audio file.

Abstract: A record including an original document and a modification to the original document is created. Metadata associated with the modification to the original document is generated. The modification in stored in a data store. Creation and registration of a decentralized identifier (DID) document for the modification is requested based on the generated metadata. Modified document metadata is generated which includes a document hash and the created DID document for the modification. Recordation of the modification in a blockchain transaction, creation and registration of a DID document for the modified document, and generation of verifiable credentials for the modification are requested. The generated verifiable credentials for the modification are stored and a quick response (QR) code for the DID document for the modification is generated. A visual representation of the modification and the QR code for the modification are added to the original document, generating a sealed document.

Abstract: Aspects of the disclosure relate to a hybrid metaverse environment. A computing platform may synchronize, using edge nodes and with a physical repository server, a soft document repository. The computing platform may receive, via a metaverse application interface, an event processing request. The computing platform may identify, based on the event processing request and using a machine learning model, documents needed to execute the event processing request. The computing platform may update a request queue to identify the event processing request and the documents. The computing platform may access, using an edge node and via the soft document repository, the physical repository server to obtain document images corresponding to the identified documents, and may update a response queue to include the obtained document images. The computing platform may send, to an enterprise user device, a haptic alert indicating that the event processing request is ready for processing.

Abstract: The present disclosure relates to cloud-based techniques that may be used to manage how digital content is arranged and distributed. For example, a non-transitory, computer-readable medium may include instructions that, when executed, are configured to cause processing circuitry to provide a cloud-based application that maintains an editable draft issue comprising a plurality of draft articles, generate a published issue that has a plurality of published articles corresponding to the plurality of draft articles based on the draft issue, and provide the published issue to one or more electronic devices.

Abstract: A computer system identifies a platform that corresponds to a first resource, wherein the first resource includes one or more resource pages. The computer system determines one or more x-paths that corresponds to the identified platform. The computer system utilizes at least a first x-path of the one or more x-paths to add a product to a digital shopping cart associated with the first resource. In response to adding the product to the digital shopping cart associated with the first resource, the computer system utilizes at least a second x-path of the one or more x-paths to access a first resource page of the one or more resource pages, wherein the first resource page is a checkout page. The computer system determines whether one or more elements located within the first resource page are valid.