A computer server system and method are disclosed for personalization and customization of network search results and rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a query from a user and transmit return queries and search results; a data storage device having a first, lexical database having one or more compilations and templates; and one or more processors configured to access the first database and search a selected compilation using the query to generate initial search results; to comparatively score each selected parsed phrase of the initial search results, for each classification of a selected template and a selected compilation, and to output initial and final search results arranged according to the classifications and the predetermined order of the template. A representative embodiment may also include use of a second, semantic database having multi-dimensional vectors corresponding to parsed phrases, paragraphs, or clauses.

A mobile apparatus receives a route response including information identifying a starting location and a target location of a route and an encoding data structure encoding the route. The encoding data structure is a probabilistic data structure configured to not provide false negatives. The mobile apparatus uses the information identifying the starting and target locations to identify a decoded origin traversable map element (TME) and a decoded target TME of the mobile version of the digital map for the route; accesses map information for determining a cost value for TMEs of the digital map, wherein a TME that satisfies the encoding data structure is assigned a minimal cost value; determines a decoded route from the decoded starting TME to the decoded target TME based on the cost value assigned to the TMEs using a cost minimization route determination algorithm; and performs at least one navigation function using the decoded route.

A system, method, and computer program product are disclosed. The method includes loading a first set of data as an initial matrix and determining a truncated singular value decomposition (SVD) of the initial matrix. The method also includes loading a second set of data as a new matrix, generating a first projection matrix, which approximates k leading left singular vectors of the updated matrix, and generating a second projection matrix, which approximates k leading right singular vectors of the updated matrix. Further, the method includes determining based on the initial matrix, the new matrix, the SVD of the existing matrix, and the first or second projection matrix, an approximate truncated SVD of the updated matrix.

A scheduler manages execution of a plurality of data-collection jobs, assigns individual jobs to specific forwarders in a set of forwarders, and generates and transmits tokens (e.g., pairs of data—collection tasks and target sources) to assigned forwarders. The forwarder uses the tokens, along with stored information applicable across jobs, to collect data from the target source and forward it onto an indexer for processing. For example, the indexer can then break a data stream into discrete events, extract a timestamp from each event and index (e.g., store) the event based on the timestamp. The scheduler can monitor forwarders' job performance, such that it can use the performance to influence subsequent job assignments. Thus, data-collection jobs can be efficiently assigned to and executed by a group of forwarders, where the group can potentially be diverse and dynamic in size.

Systems and methods for generating and annotating cell documents include extracting tables from a document using a table extraction engine. Headers are extracted for each of the tables using a header detection engine. Cells are extracted from each of the tables using a cell extraction engine. A cell document is generated for each of the cells which are each correlated to corresponding portions of the headers, each cell document recording the correlation between the cells and the headers. Each cell document is annotated to generate annotated cell documents with a cell recognition model trained to perform natural language processing on the cell documents by classifying each term in each of the cell documents and extracting relationships between the terms of each of the cell documents.

Computer-readable media, methods, and systems are disclosed for storing and analyzing dynamic data within a semantic data store. The dynamic data comprises one or more types of data having a normalized data schema. A dynamic data manager interfaces with the semantic data store to instruct storage of the data. The data may be received through an event service from either of an external data source or an internal data source.

Documents, such as those that may or will be the subject of a litigation, may be managed by automatically determining that a document, such as an email or other communication, is privileged or producible such that superfluous documents may be removed to improve data storage and reduce the burden on storage, processing, and communication resources. Additionally, documents such as emails may comprise attached or embedded documents (e.g., attachments) which may be similarly or independently classified from their associated email. After determining privilege, such as via metadata associated with a sender/receiver of an email, similarly categorized documents may be grouped for presentation and/or storage. The documents may be indexed, such as by entries within a production log, to further facilitate accurate production and management of non-privileged documents, as well as, the exclusion of privileged documents. Documents not required for production may be indexed and/or purged from storage.

Systems, methods, and computer program products may be configured to generate a set of related document objects for a predictive entity and/or to generate an optimal document sequence for a set of related document objects. In one embodiment, for example, a set of related document objects for a predictive entity is generated by processing entity metadata features associated with the predictive entity using an entity-document correlation machine learning model, and an optimal document sequence is generated for the set of related document objects by processing the set of related document objects using a document sequence optimization machine learning model.

Methods, systems, and apparatus for determining that a native application limits access to the native application using account credential requirements, the native application generating an application environment for display on a user device within the native application and operating independent of a browser application that can operate on the user device; obtaining a set of account credentials for indexing environment instances of the native application; instantiating the native application with the set of account credentials; and accessing environment instances of the native application, and for each of the environment instances: generating environment instance data describing content of the environment instance, the content described by the environment instance data including text that a user device displays on the environment instance when the user device displays the environment instance; and indexing the environment instance data for the native application in an index that is searchable by a search engine.

Techniques for database performance degradation detection and prevention are described. A statement performance monitor observes queries executed against a database engine and clusters the queries into groups of queries. The index utilization of the query groups and execution metrics are tracked over time, and a sudden change of index utilization can be detected. The change can be reported to users and/or new indexes may be automatically generated to serve affected query groups. Additionally, a statement performance monitor may be deployed to statically analyze code to identify modified queries and the resultant change of use of query indexes.