Abstract: The present disclosure provides systems and methods for content quasi-personalization or anonymized content retrieval via aggregated browsing history of a large plurality of devices, such as millions or billions of devices. A sparse matrix may be constructed from the aggregated browsing history, and dimensionally reduced, reducing entropy and providing anonymity for individual devices. Relevant content may be selected via quasi-personalized clusters representing similar browsing histories, without exposing individual device details to content providers.

Abstract: Embodiments as disclosed herein provide a search system with an pre-indexing filter that provides both a sophisticated and contextually tailored approach to filtering documents and a corrector that is adapted to alter a document that has been designated to be filtered out from the indexing process and determine if the altered document should be indexed. The alteration of the document may be tied to the attributes, rules or thresholds used to initially filter the document from the indexing process. The filtering criteria can thus be tailored to a specific context such that both the initial filtering and the alteration process may be better suited for application in that context.

Abstract: An apparatus includes an interface and a processor. The interface sends and receives data over a network. The processor uses the interface to transmit a first media file to a device of a user. The first media file presents a first choice between at least two options. The processor uses the interface to receive from the user a first selection in response to the first choice. In response to receiving the first selection, the processor transmits a second media file to the device. The second media file presents a second choice between at least two options. The processor uses the interface to receive from the user a second selection in response to the second choice. The processor identifies, based in part on the first selection and the second selection, a second user as potentially compatible with the user and transmits to the user a profile of the second user.

Abstract: A computer-implemented method comprises analyzing content sections on each of a plurality of open browser pages using natural language processing to identify one or more topics on each of the plurality of open browser pages; calculating a respective relevance score for each of the content sections; grouping each of the plurality of topics into one of a plurality of topic groups; calculating a respective group ranking for each of the plurality of topic groups based on the respective relevance score for each content section. The method further comprises, for each topic group, assigning the respective group ranking to all of the content sections corresponding to the respective topic group; and, for each of the plurality of open browser pages, selecting at least one content section having a highest group ranking and modifying a display of the respective open browser page to direct attention to the selected content section.

Abstract: There is provided a method and a system for generating clusters of documents using a combined metric parameter. A first document and a second document are received, and for a potential cluster including the first document and the second document: a first metric parameter indicative of a degree of complementariness of document content in the potential cluster is determined, a second metric parameter indicative of a degree of dilution of the document content in the potential cluster is determined. The combined metric parameter is determined based on the first metric parameter and the second metric parameter. A cluster is generated based on the combined metric parameter, where the cluster includes the first and second documents. Other document(s) or clusters may be added to the cluster by determining an updated combined metric parameter for a potential cluster and comparing the updated combined metric parameter with the combined metric parameter.

Abstract: Systems and techniques for leveraging query executions to improve index recommendations are described herein. In an example, a machine learning model is adapted to receive a first query plan and a second query plan for performing a query with a database, where the first query plan is different from the second query plan. The machine learning model may be further adapted to determine execution cost efficiency between the first query plan and the second query plan. The machine learning model is trained using relative execution cost comparisons between a set of pairs of query plans for the database. The machine learning model is further adapted to output a ranking of the first query plan and second query plan, where the first query plan and second query plan are ranked based on execution cost efficiency.

Abstract: A computer-implemented method for content-agnostic referencing of a binary data file, the method comprising: pregenerating a table of all permutations of data of a particular length, determining a length of the binary data file, the length comprising the number of bits of the binary data file; chunking the binary data into chunks of data of a smaller length; for each chunk, determining if the chunk is in the pregenerated table, and if so using that chunks index in the pregenerated table, and otherwise chunking the data again until the sub-chunks are located in the pregenerated table, and using the number of chunks and associated indices to indicate the binary data file.

Abstract: A method includes searching an initial set of documents for an initial set of query names. Each query name of the initial set of query names is associated with at least one document of the initial set of documents. The method also includes prioritizing the initial set of query names based on at least one topic label. The method also includes searching an additional set of documents to generate candidate query names. The method also includes prioritizing the candidate query names based on the at least one topic label. The method further includes applying a temporal search filter to each candidate query name to determine whether the candidate query name was processed within a time frame. The method further includes performing disambiguation processing on each candidate query name not processed within the time frame.

Abstract: A method for analyzing a thought system is described. One or more keywords and a degree of relation between each of the one or more keywords are obtained. An N×N matrix based on the one or more keywords and the degree of relation between each of the one or more keywords are determined. (N?1) eigenfunctions having N-dimensional components and (N?1) eigenvalues is determined from the N×N matrix using the wave equation for quantum theory. A graphical representation based on the (N?1) eigenfunctions and the (N?1) eigenvalues is generated.

Abstract: Techniques are described herein for intelligent pooling and management of isolated hierarchical runtimes in a multi-tenant environment. In an embodiment, an allocation of operating system resources of a container database management system (CDBMS) is allocated to each generic nest of a pool of generic nests. The allocation includes a quota of one or more processors and a quota of memory. A configuration profile for a PDB in the CDBMS is then determined. Based on the configuration profile determined for the PDB, a matching generic nest from the pool of generic nests is determined. A matching generic nest is assigned to the PDB. The matching generic nest is then configured for the PDB.

Abstract: A method includes acquiring data from sources of search query data. The data indicates searches performed at multiple search engines. The method includes identifying a set of search terms from the data, determining a number of times each of the identified set of search terms was searched, and generating a search count for each of the identified set of search terms based on the number of times each of the identified set of search terms was searched. The method includes classifying, based on predetermined criteria, the searches for the identified set of search terms as being active or passive, assigning weights according to predetermined rules to each of the searches based on whether each of the searches is active or passive, and generating weighted search counts by multiplying the search counts with respective weights. The method includes generating a score indicating an interest level in the first search term.

Abstract: A building management system (BMS) includes building equipment configured to provide raw data samples of one or more data points in the BMS. The BMS further includes a data collector configured to collect raw data samples from the building equipment and generate one or more raw data timeseries comprising a plurality of the raw data samples. The BMS also includes a timeseries processing engine. The timeseries processing engine is configured to identify one or more timeseries processing workflows that apply to the raw data timeseries, each of the workflows comprising a predefined sequence of timeseries processing operation. The timeseries processing engine is further configured to process the raw data timeseries using the identified timeseries processing workflows to generate one or more derived data timeseries. The BMS further includes a timeseries storage interface configured to store the raw data timeseries and the derived data timeseries in a timeseries database.

Abstract: A storage unit (SU) includes an interface configured to interface and communicate with a dispersed storage network (DSN), a memory that stores operational instructions, and processing circuitry operably coupled to the interface and to the memory. The processing circuitry is configured to execute the operational instructions to perform various operations and functions. The SU, of a first SU set, receives a partially encoded slice request to restore a set of encoded data slices (EDSs) that are based on first dispersed storage error coding function parameters. The SU generates a decode threshold number of partially EDSs based on the first and second dispersed storage error coding function parameters. The SU then outputs the decode threshold number of partially EDSs to a second SU set to undergo selective combination respectively to generate new EDSs for storage within the SUs of the second decode threshold number of SUs of the second SU set.

Abstract: A query having a Union All view is identified. A logical join between Union AH view/derived table and other tables is broken down into multiple physical joins. The physical joins are pushed to the branches. Cost-based processing statistics are obtained for the branches. An optimal plan for the joins is selected based on the statistics; representing an optimal query execution for the query. The optimal query execution plan is provided to a database engine for executing the optimal query execution plan against a data warehouse.

Abstract: An approach is provided that analyzes electronic document sets, each of the sets written by a different author. The analysis includes performing a normalized sentiment analysis of the documents which results in normalized sentiment scores that pertain to each of the authors. The normalize sentiment scores are stored in a data store that is accessible from a question answering (QA) system. The question answering system then receives a sentiment-based question. Responsively, the QA system generates a qualitative set of candidate answers, with the candidate answers based at least in part on the normalized sentiment scores retrieved from the data store.

Abstract: A method and system are disclosed for performing real-time analytics on a plurality of data streams, the method comprising obtaining a plurality of data streams; accumulating real-time changes of the obtained plurality of data streams in a buffer unit to provide a buffered data portion; monitoring the buffered data portion for determining a calculation event, wherein the calculation event is based on a strategy based on observing given features in the buffered data portion; upon detection of the calculation event, generating an optimization problem indicative of the real-time analytics to be performed on one of given data portions of the plurality of data streams and a data structure generated using given data portions of the plurality of data streams; transforming the generated optimization problem into an optimization problem suitable for an optimization oracle; providing the transformed generated optimization problem to the optimization oracle; obtaining at least one solution from the optimization oracle;

Abstract: A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.

Abstract: Disclosed is a system and method for efficient comparison of experimental research documents to identify original research work. The system when operated, provides a platform for comparing a user submitted document with documents existing in the platform and documents available in public domain. Further, the system is capable of identifying originality and the similarity of the user submitted documents, in comparison with existing documents, based on a calculated similarity index.

Abstract: Systems and methods for managing blockchain nodes. Blockchain node clusters are created and used to process blockchain requests. Blockchain clusters are managed by adding nodes to a cluster, stopping nodes in the cluster, and generating snapshots of state. of one or more nodes.

Abstract: An example implementation may relate to an apparatus that may identify data content of interest from data in buffers, and may store index entries representing the identified data content in a hierarchical index having different performance levels. The apparatus may include a priority manager that maintains an index scoreboard that tracks where index entries are to be stored among the different performance levels of the hierarchical index based on predetermined polices that prioritize data content of interest or functions that use data content of interest.