Abstract: Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations by determining semantic connections between the semantic annotations and then dynamically generating a topic page based on the semantic connections.

Abstract: Content of different formats may be sourced from various data sources such as content servers and ingested into a data integration server by an ingestion broker embodied on a non-transitory computer readable medium. The ingestion broker may normalize the content of different formats into a uniform representation that can be indexed and delivered across multiple digital channels for a variety of applications. The normalized content may be analyzed and semantic metadata may be determined from the normalized content. The normalized content can be semantically enriched by associating the semantic metadata and the like with the content. The semantic metadata can be stored in a semantic index that can be used for searching via the data integration server. During search, the semantic metadata can be instantiated as facets for user navigation and refinement of search criteria and additional semantic relationships can be assigned to the words in the normalized content.

Abstract: In an auto-classification system, example documents whose content exemplifies a content category or classification can be imported into a classification model. The classification model is tested to assess accuracy. Based on the testing, metrics or other information can be provided as feedback to a user. The user can iteratively refine the classification model and keep re-running the classifications to view how each change to the classification model improves accuracy. If no user refinement is desired, the auto-classification system classifies documents utilizing the classification model. This technology enhances the overall transparency and defensibility of the auto-classification process.

Abstract: The present disclosure provides the quantification of double-strand breaks in DNA molecules using terminal deoxynucleotidyl transferase using a preliminary step of nick gap and repair. This preliminary step comprising contacting the DNA molecules with both a DNA ligase and a DNA polymerase to repair DNA nicks and remove DNA gaps prior to using the terminal deoxynucleotidyl transferase.

Abstract: Systems and methods include obtaining performance monitoring data from a network which operates and generates the performance monitoring data which reflects a current state of the network; responsive to a predetermined reward which quantifies minimizing or maximizing an aspect in the network for Reinforcement Learning, causing one or more actions to be performed in the network, wherein the one or more actions are based on the predetermined reward; obtaining updated performance monitoring data from the network subsequent to the one or more actions to determine an updated state of the network; and continuing the causing the one or more actions to be performed in the network based on the current state and the updated state. The causing the one or more actions to be performed in the network is performed to maximize or minimize a total discounted accumulated reward.

Abstract: Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations by determining semantic connections between the semantic annotations and then dynamically generating a topic page based on the semantic connections.

Abstract: An auto-classification system and method provides dynamic user feedback in a guide that is presented to the user. The feedback presented in the guide enables the user to refine the classification model by adding or removing exemplars, creating, editing or deleting rules, or performing other such adjustments to the classification model. This technology enhances the overall transparency and defensibility of the auto-classification process.

Abstract: Systems and methods implemented by a computer to detect abnormal behavior in a network include obtaining Performance Monitoring (PM) data including one or more of production PM data, lab PM data, and simulated PM data; determining a model based on machine learning training with the PM data; receiving live PM data from the network; utilizing the live PM data with the model to detect an anomaly in the network; and causing an action to address the anomaly.

Abstract: An auto-classification system and method provides dynamic user feedback in a guide that is presented to the user. The feedback presented in the guide enables the user to refine the classification model by adding or removing exemplars, creating, editing or deleting rules, or performing other such adjustments to the classification model. This technology enhances the overall transparency and defensibility of the auto-classification process.

Abstract: Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations by determining semantic connections between the semantic annotations and then dynamically generating a topic page based on the semantic connections.

Abstract: An auto-classification system and method provides dynamic user feedback in a guide that is presented to the user. The feedback presented in the guide enables the user to refine the classification model by adding or removing exemplars, creating, editing or deleting rules, or performing other such adjustments to the classification model. This technology enhances the overall transparency and defensibility of the auto-classification process.

Abstract: Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations by determining semantic connections between the semantic annotations and then dynamically generating a topic page based on the semantic connections.

Abstract: An auto-classification system and method provides dynamic user feedback in a guide that is presented to the user. The feedback presented in the guide enables the user to refine the classification model by adding or removing exemplars, creating, editing or deleting rules, or performing other such adjustments to the classification model. This technology enhances the overall transparency and defensibility of the auto-classification process.

Abstract: Content of different formats may be sourced from various data sources such as content servers and ingested into a data integration server by an ingestion broker embodied on a non-transitory computer readable medium. The ingestion broker may normalize the content of different formats into a uniform representation that can be indexed and delivered across multiple digital channels for a variety of applications. The normalized content may be analyzed and semantic metadata may be determined from the normalized content. The normalized content can be semantically enriched by associating the semantic metadata and the like with the content. The semantic metadata can be stored in a semantic index that can be used for searching via the data integration server. During search, the semantic metadata can be instantiated as facets for user navigation and refinement of search criteria and additional semantic relationships can be assigned to the words in the normalized content.

Abstract: Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations by determining semantic connections between the semantic annotations and then dynamically generating a topic page based on the semantic connections.