Abstract: Systems and methods for reconstructing a namespace in response to a loss of data are described herein. To reconstruct the namespace, metadata super segments within a set of file containers may be located in response to a determination that original namespace metadata associated with files stored within the containers is unreadable. Content handles linking the super segment to metadata for each of the files may then be reconstructed from the super segments. Both inode numbers and M-tree identifiers are also extracted from the super segments for each of the files referenced by the super segments. Then, a plurality of U-trees is assembled by aggregating and linking the inode numbers of the files referenced within the super segments based on the M-tree identifiers. Finally, the recovered namespace metadata tree data structure for all of the files within the plurality of LP containers is assembled by aggregating and linking the U-trees.

Abstract: Described herein are systems and methods for profiling structured or semi-structured datasets. An example computer-implemented method includes grouping, using a machine learning classifier, a plurality of tables in a dataset that are associated with an object into a cluster, where each of the tables of the cluster includes respective data and respective metadata, the respective metadata including at least one respective attribute, generating a metadata-profile for the cluster, where the metadata-profile includes the at least one respective attribute of each of the tables of the cluster; and querying the cluster using the metadata-profile.

Abstract: A method, computer program product, and computer system for maintaining, by a computing device, mapper objects, wherein the mapper objects may be variable size and include tops, mids, and leafs. Only new pointers may be maintained inside successor tops and mids. An overwrite map structure may be maintained on each of the tops, mids, and leafs. In the overwrite map structure on a mid, a snapshotID of a leaf that was last updated may be provided, from which the mid is to be inherited based upon a received IO.

Abstract: Systems and processes are directed to: annotating Internet search results to indicate missing search term elements on referenced and descendant webpages; optionally filtering out search results referencing webpages with missing terms; and showing advertisements co-visible with annotated search results. When shown, annotations warn the user to avoid clicking on an Internet search result where the user's search term elements are not present on referenced and/or descendant webpages, thereby preventing wasted time and speeding the search process.

Abstract: Event detection may be carried out to determine one or more content items associated with an event type. A server may determine one or more visually relevant labels, of a plurality of labels, associated with the event type. The server may determine one or more textually relevant labels, of the plurality of labels, associated with the event type. The server may determine an event label distribution based on a correlation of the visually relevant event labels and the textually relevant labels, wherein the event label distribution comprises a plurality of labels. The server may determine a content item label distribution associated with a content item, wherein the content item label distribution comprises a plurality of second labels. The server may send, based on comparing the event label distribution with the content item label distribution, the content item to a computing device.

Abstract: The disclosure provides a non-opaque, abstract, unified query language that exposes the query as a first-class citizen of the underlying architecture. The present disclosure thus facilitates the creation of no-code or low-code applications by enabling a level of collaboration between components that may be difficult to achieve if the language employed were opaque to the architecture. The disclosed query language may be considered “SQL-like,” which may allow contributors familiar with structured query language (SQL) to effectively participate in the design of an application. The defined structures of a data objects of the non-opaque query language described herein are not-hidden and inspectable.

Abstract: A search engine optimizer which works independently and in parallel with a browser and search engine supercomputer to gather, analyze, and distill input information interactively. The optimizer reorganizes the input, and providing an optimized version as an output. The optimized version of the input (e.g. output) is sent to the search engine which responds to the end user with search results. The optimizer recognizes each request as a pattern and stores the pattern in an advanced Glyph format. This permits the optimizer to identify a left and ride side check mate combination required to achieve certitude.

Abstract: Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.

Abstract: A computer-implemented method is provided that includes accessing candidate text and a candidate pair including first and second phrases, substituting the first and second phrases into cause-effect patterns to generate variant sentences. An artificial intelligence model is leveraged to determine respective probabilities that the variant sentences are inferred from the candidate text, calculate a statistical measure of the respective probabilities, and assess the calculated statistical measure to ascertain whether the first and second phrases possess a causal relationship or non-causal relationship to one another. A knowledge base including one or more pairs of cause-effect phrase pairs is populated with the first and second phrases possessing the causal relationship. A computer system and a computer program product are also provided.

Abstract: A system and method of data record management is provided. The system comprises a processor and a memory coupled to the processor that stores processor-executable instructions that when executed configure the processor to perform the method. The method comprises receiving a plurality of unstructured natural language data records, generating a structured dataset based on the plurality of unstructured natural language data records, transforming the structured dataset to normalize the respective frequency values based on inverse proportionality of the respective frequency values, determining a redundancy prediction value associated with that unstructured natural language data record based on the transformed structured dataset, and displaying on a graphical user interface a message identifying one or more unstructured natural language data records being associated with a redundancy prediction value greater than a threshold value.

Abstract: Various embodiments are directed to a system that utilizes regular expression (regex) to recognize at least portions of characters, words, text, numbers, etc. in a structured or unstructured dataset, any patterns associated therewith, and/or similarities between the determined patterns. In examples, a regex-based pattern recognition platform may receive a dataset and determine whether at least a first regex pattern and a second regex pattern can be identified. The occurrences of the first and second regex patterns and the frequency of those occurrences may reveal something about the dataset itself or any patterns contained therein.

Abstract: A computerized method for training a computer executed model for recognizing numerical quantities is provided. An input, at least one unit expression, is received by an input module. The input module may then search for numeric values and the unit expression in a text corpus, wherein, the text corpus comprises sets of words and frequency of occurrence of each of the sets. The input module may identify identified sets, wherein the identified sets may comprise a combination of a numeric value and the unit expression. A synthetic text generation module may then generate sentences from the text corpus by applying the identified sets as input. A training dataset may be generated by a labeling module by auto labelling features in the generated sentences based on the numeric value and the unit expression and further a training module may train the training model by providing input based on the training dataset.

Abstract: Techniques for grouping system logs using machine learning. The techniques include deriving an input matrix from the logs, in which rows represent the logs and columns represent unique words in the logs. The techniques include applying a TF-IDF algorithm to the input matrix and deriving a TF-IDF matrix from the TF-IDF algorithm output. The TF-IDF matrix reflects how important the unique words are to the respective logs. The techniques include applying a PCA algorithm to the TF-IDF matrix and deriving a PCA matrix having a reduced dimensionality from the PCA algorithm output. The techniques include applying a Cosine Similarity algorithm to the PCA matrix and deriving CS matrices from the CS algorithm output. Each CS matrix reflects the cosine similarity of a respective log relative to all the other logs. The techniques include applying a clustering algorithm to the CS matrices and deriving log groupings from the clustering algorithm output.

Abstract: A method for responding to a query is implemented on at least one computing device and includes: receiving at least one query from a user device; determining a context for the at least one query, selecting at least one deep learning network (DLN) of a plurality of DLNs to process the at least one query, where the selecting is based at least on matching the context to the at least one DLN, sending at least a representation of the at least one query and the context to the at least one DLN, receiving at least one response to the at least one query from the at least one DLN, and sending the at least one response to the user device.

Abstract: One or more computing devices, systems, and/or methods are provided. In an example, a first performance metric score may be determined based upon first content item text. A plurality of similarity scores associated with a plurality of sets of content item text may be determined. One or more sets of content item text may be selected from among the plurality of sets of content item text based upon the plurality of similarity scores and a plurality of performance metric scores associated with the plurality of sets of content item text. The plurality of performance metric scores may comprise one or more performance metric scores associated with the one or more sets of content item text. The one or more performance metric scores may be higher than the first performance metric score. One or more representations of the one or more sets of content item text may be displayed.

Abstract: A method for classifying patent documents may include the steps of learning patent documents stored in a patent database by machine learning technology, establishing a first classification standard based on similarity between the patent documents, and generating a basic classification model of classifying the patent documents based on the first classification standard; generating a patent pool including a plurality of patent documents based on a search and/or selection input of the user; receiving the classification input of the user and classifying the plurality of patent documents included in the patent pool according to the classification input; predicting a second classification standard classifying the plurality of patent documents by the user based on the similarity between the classified patent documents; and classifying remaining patent documents which are not yet classified in the patent pool based on the basic classification model and the second classification standard.

Abstract: Systems and methods are described for identifying a target entity that a user intends to refer to based on input that may include only a partial name of the entity. A system may receive a user's entity search query, which may include a partial entity name, then may determine initial candidate matching entities and associated name match scores for each of the initial candidate matching entities relative to the input string, such as using string matching or fuzzy matching techniques. The system may apply a probability match model to generate an overall match score for individual ones of the initial candidate matching entities, then may generate a response to the entity search query that includes information regarding one or more of the initial candidate matching entities with an overall match score exceeding a threshold.

Abstract: Methods, apparatus and computer program product that may include receiving, by one or more servers of a group-based communication platform and from a client of a first user with administrative privileges and associated with a first organization, a request to generate a shared communication channel on the group-based communication platform. A shared communication channel may be generated based on the request. A second request may be received by the one or more servers to provide at least one second user associated with a second organization access to the shared communication channel. Access may be provided to the second user. A message communication may be rendered in a shared communication channel interface associated with the shared communication channel with a graphical indicator that indicates the message communication is associated with the first organization.

Abstract: Improved artificial intelligence computer systems actively and/or passively provide end-users with information from firm data systems to help the end-user perform the end-user's job functions. In a passive implementation, the system can prioritize emails for a user, craft consistent responses to multiple email inquiries on the same topic, and/or craft responses whose content is drawn from a library of electronic documents. In an active implementation, the system comprises AI agents associated with individual databases of the system, where the AI agents are tuned to retrieve data from their associated database in response to a query from the end-user.

Abstract: At least one table included in first content may be determined. The at least one table includes a first plurality of rows and a first plurality of columns. It may be determined that a first term indicative of a personal name is included in a first row of the first plurality of rows and a first column of the first plurality of columns. A second row of the first plurality of rows that includes at least a first personal name in the first column and a first item of personal identifying information in a second column of the first plurality of columns may be identified. First data indicative of the first personal name and the first item of personal identifying information may be extracted. The first data may be added to a first profile associated with the first personal name.