Abstract: The present disclosure is directed to systems and methods for recognizing and categorizing documents. In some embodiments, a computing system can access an archetype template and a corresponding label for each targeted category. The computing system can analyze a set of target binary documents based on a set of sequenced and contextually triggered hashing operations. The target binary documents can be categorized based on comparing the analysis results to the archetype templates or results derived from the archetype templates.

Abstract: In one embodiment, a method includes, by a client system, receiving, by an assistant xbot of the client system, a request from a first user for a summary of user content from a first content source, retrieving, from the first content source, a plurality of content items corresponding to the request, generating a personalized summary of the retrieved content items, wherein the personalization of the summary is based on a user profile of the first user, and presenting, by the assistant xbot, the personalized summary responsive to the request within a separate communication interface between the assistant xbot and the first user, wherein the personalized summary is interactable by the first user to react to one or more of the plurality of content items.

Abstract: Technologies are provided for automated generation of revision summaries for an electronic document. In some embodiments, a computing system can determine that a first section of a first version of the electronic document includes changes relative to a second section of a second version of the electronic document. The second section corresponds to the first section. The computing system also can generate respective descriptions of the first section and the second section. The computing system can then generate a summary of the changes by comparing the respective descriptions. The computing system can determine that the summary has a defined placement in a ranking of similarity scores, where a first similarity score in the ranking defines similarity between the respective descriptions. The computing system can add metadata to the first version of the electronic document. The metadata controls presentation of a visual element indicative of the summary within a user interface.

Abstract: A method of generating recommendations for a collective profile, the collective profile being linked to a first profile and a second profile. The method may include authenticating a login request from an end user device in association with the collective profile based on credentials associated with the first profile, identifying a query from among a plurality of queries and transmit the query to the end user device, receiving a response to the query, determining that the response is not inconsistent with one or more earlier responses received in association with the second profile and, in response, refining at least one attribute or goal in the collective profile based on the response to generate and store a refined collective profile, and determining whether the refined collective profile results in a new recommendation and, if so, outputting the new recommendation.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and cause the one or more processors to perform functions comprising: tracking interaction data for one or more webpages of a website; determining a content score for the one or more webpages of the website; determining a link equity score for the one or more webpages of the website; classifying the one or more webpages of the website into one or more classifications using the interaction data, the content score, and the link equity score; and removing the one or more webpages from a sitemap of the website based on the one or more classifications. Other embodiments are disclosed herein.

Abstract: Systems, media, and methods for automated response to social queries comprising: monitoring queries from users, each query submitted to a vendor via an interactive chat feature of an external electronic communication platform, monitoring human responses to the queries, monitoring subsequent communications conducted via the electronic communication platform until each query is resolved; applying a first machine learning algorithm to the monitored communications to identify a query susceptible to response automation; applying a second machine learning algorithm to the query susceptible to response automation to identify one or more responses likely to resolve the query; and either i) notifying a human to respond to the query susceptible to response automation with the one or more responses likely to resolve the query, or ii) instantiating an autonomous software agent configured to respond to the query susceptible to response automation with the one or more responses likely to resolve the query.

Abstract: Techniques and systems are provided for predicting answers in response to one or more input queries. For instance, text from a corpus of text can be processed by a reader to generate one or multiple question and answer spaces. A question and answer space can include answerable questions and the answers associated with the questions (referred to as “question and answer pairs”). A query defining a question can be received (e.g., from a user input device) and processed by a retriever portion of the system. The retriever portion of the system can retrieve an answer to the question from the one or more pre-constructed question and answer spaces, and/or can determine an answer by comparing one or more answers retrieved from the one or more pre-constructed question and answer spaces to an answer generated by a retriever-reader system.

Abstract: A technique for data sharing among multiple filers that share a volume in a private or public cloud object store is implemented. In this approach, a mechanism is provided to enable a local filer to determine whether other filers that are sharing the volume have a consistent view of new data being written to the cloud object store by the local filer. The begins by associating together a collection of one or more files in a “push class.” On demand, a push operation for the push class is initiated on the local filer. Preferably, the push is managed according to one or more push criteria associated with the push class. Typically, the push operation pushes file data and metadata associated with the one or more files of the push class in respective phases, with the file data being pushed to the cloud during a first phase and the metadata associated with that file data being pushed during a second phase that follows the first phase.

Abstract: Methods, apparatus, systems and articles of manufacture to monitor media are disclosed. An example apparatus includes at least one memory, first instructions in the apparatus, and processor circuitry to execute the first instructions. The first instructions, when executed, are to: instruct a media provider to include second instructions in an application to create an instrumented application and receive data from a media device based on the media device executing the second instructions.

Abstract: Creating and executing flow plans by performing at least the following: obtaining a run-time flow plan that comprises a trigger, a first operation, and a second operation, wherein the first operation precedes the second operation within the run-time flow plan and one or more input values of the second operation are linked to the first operation, determining whether one or more conditions of the trigger are met, execute the first operation based at least on the determination that the one or more conditions of the trigger are met, monitoring whether the second operation is ready for execution based at least on a determination that the one or more input values of a second action operation are ready, and executing the second action operation when the second action operation has been identified as ready for execution.

Abstract: Users of electronic audio and video playback devices have become familiar with listening and viewing media from stored memory. Music may be listened to and any art may be viewed including television, motion pictures, still images and any other copyrightable works of audible or visual art, the types of which are vast. Traditional indexing criteria for such stored memory may include artist or author identification, track or work of art title, genre, era or origin, style of art, and other criteria pertaining to the work itself. According to the present invention, media elements stored in memory may now be characterized by entering criteria based on the qualitative attributes and emotive features ascertained upon playback or subsequent evaluation which are then associated with each stored audio, video, image or other file, for subsequent indexing, searching and recommendation operations.

Abstract: A database management system stores data for a table as a journal of transaction. The records of the journal comprise information indicative of changes applied to a document of the table. The database receives a query on a table of transactions performed on the table. In response to the query on the table of transactions, the database generates results by retrieving and projecting the records of the journal in accordance with the query. The results of the query are indicative of changes applied to the document of the table.

Abstract: Computer systems configured to correlate instances of empirical data, gathered from ambient observation of a person, as being potentially relevant to each other vis-à-vis one particular behavior. In a behavior-identification-process, a pair of correlated instances of empirical data is analyzed to identify it as an instance of the one particular behavior. Such computer systems facilitate transmission of a digital message, the content of which may be determined in response to the instance of the one particular behavior. The content of some digital messages may include experiments performed by such computer systems on the person, to test the validity of the behavior-identification-process. The behavior-identification-process can then be updated with the observed responses of the person, and with the results of the experiments. These experiments and the updating of the behavior-identification-process might be performed by such computer systems to autonomously refine the behavior-identification-process.

Abstract: A plurality of histograms are maintained with respect to a dataset. The dataset includes a plurality of data segments. In response to a query that includes a plurality of conditions ordered in an initial sequence, a plurality of corresponding rejection rates is determined for the plurality of conditions based at least in part on the plurality of histograms. The plurality of conditions are re-ordered according to the plurality of corresponding rejection rates associated with the plurality of conditions to form a reordered sequence for the plurality of conditions. The query is executed according to the reordered sequence of the plurality of conditions.

Abstract: Techniques facilitating tree-based associative data augmentation are provided. In one example, a computer-implemented method comprises: generating, by a device operatively coupled to a processor, a model probability distribution for one or more measured samples based on conditional probabilities for respective nodes of a tree structure associated with dimensions of the one or more measured samples; and producing, by the device, synthetic samples by drawing from the model probability distribution for at least one of the one or more measured samples.

Abstract: A method by a network device to enrich database logs. The method includes detecting that a process executing on the network device has created a database connection to a database server, determining contextual information of the process in response to detecting that the process has created the database connection, generating a key associated with the database connection based on information that is known to be included in a database log of the database, and providing the key and the contextual information to a correlator component.

Abstract: A method includes: a first node and a second node in a distributed computing system each creating a respective partial join filter; the first node and the second node each transmitting its respective partial join filter to a third node in the distributed computing system; the third node creating a final join filter by combining the respective partial join filters of the first node and the second node; the third node retrieving target data from a data source of the third node by applying the final join filter to the data source of the third node; and the third node transmitting the retrieved target data to a controlling node in the distributed computing system.

Abstract: Methods and systems allow organizations to discover accounts, subscriptions, properties, sites and other online portals within each distinct social network platform and across disparate social network platforms, publishing platforms and networks that represent, claim to represent or are relevant to their organization and/or brands based on search terms and facilitate the statistical reporting and analysis of activities on the discovered properties.

Abstract: Among other things, a machine-based method is described. The method comprises recording object classes of an object model, producing an object representation for data of two or more data sources based on a mapping of data formats of the data sources to the object classes of the object model, and producing mapped data from the data sources. The mapped data is available in objects of the object classes and is comparable in the object representation. At least two of the data sources have different data formats.

Abstract: The disclosed systems and methods include pre-calculation, per object, of object feature bin values, for identifying close matches between objects, such as text documents, that have numerous weighted features, such as specific-length word sequences. Predetermined feature weights get scaled with two or more selected adjacent scaling factors, and randomly rounded. The expanded set of weighted features of an object gets min-hashed into a predetermined number of feature bins. For each feature that qualifies to be inserted by min-hashing into a particular feature bin, and across successive feature bins, the expanded set of weighted features get min-hashed and circularly smeared into the predetermined number of feature bins. Completed pre-calculated sets of feature bin values for each scaling of the object, together with the scaling factor, are stored for use in comparing sampled features of the object with sampled features of other objects by calculating an estimated Jaccard similarity index.