Abstract: Embodiments are provided for unsupervised learning of domain specific knowledge graph from textual data and language generation from knowledge graph via reinforcement learning in a computing system by a processor. Unstructured data is automatically parsed into one or more knowledge graphs based on the unstructured data and a list of candidate relations using a first machine learning model. Text data is generated from the one or more knowledge graphs using a second machine learning model.

Abstract: Embodiments described herein relate to techniques for route control. The techniques may include obtaining, by a routing information base (RIB) agent, a route policy for performing a route action; receiving, by the RIB agent, a route from a routing protocol; analyzing, by the RIB agent, the route using to make a determination about whether to perform the route action; and performing, by the RIB agent, the route action based on the determination. Route actions may include actions relating to route modification, route redistribution, modifications of various attributes of a route, etc.

Abstract: Data security across data residency restriction boundaries is provided by obtaining and profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, then automatically generating a container image based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, the container image configured for instantiation and execution to process the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, and storing the container image to a container registry.

Abstract: Embodiments for providing an enhanced codebase in a computing environment by a processor. One or more container specification files may be automatically generated for a codebase based on one or more extracted attribute names and values.

Abstract: Embodiments for automatic data preprocessing for a machine learning operation by a processor. For each data instance in a set of data instances, a sequence of actions may be automatically learned in a reinforcement learning environment to be applied for preprocessing each data instance separately. Each of the data instances may be preprocessed for use by one or more machine learning models according to the learned sequence of actions.

Abstract: Compositions and methods for the treatment of viral infections include conjugates containing inhibitors of viral neuraminidase (e.g., zanamivir, peramivir, or analogs thereof) linked to an Fc monomer, an Fc domain, and Fc-binding peptide, an albumin protein, or albumin-binding peptide. In particular, conjugates can be used in the treatment of viral infections (e.g., influenza viral infections).

Abstract: Compositions and methods for the treatment of viral infections include conjugates containing inhibitors of viral neuraminidase (e.g., zanamivir, peramivir, or analogs thereof) linked to an Fc monomer, an Fc domain, and Fc-binding peptide, an albumin protein, or albumin-binding peptide. In particular, conjugates can be used in the treatment of viral infections (e.g., influenza viral infections).

Abstract: Provided are a provisioning method for cloud service and a system thereof. The provision method according to some embodiments may include collecting a resource utilization rate of each of a plurality of cloud nodes, receiving a regular instance request from a client, determining whether there is a cloud node among the plurality of cloud nodes that satisfies a first condition, in which the collected resource utilization rate is less than a first threshold value, designating a specific cloud node from among the plurality of cloud nodes based on a determination that there is no cloud node that satisfies the first condition, and terminating at least some of spot instances pre-provisioned on the specific cloud node and provisioning a requested regular instance.

Abstract: Embodiments are provided for providing predictive computing and data analytics for project management in a computing system by a processor. A lifecycle of each of a plurality of objects may be monitored based on data received from a plurality of data sources. Predictive analytics for project management of each of the plurality of objects may be provide based on monitoring the lifecycle of each of the plurality of objects.

Abstract: Embodiments described herein relate to techniques for route control. The techniques may include obtaining, by a routing information base (RIB) agent, a route policy for performing a route action; receiving, by the RIB agent, a route from a routing protocol; analyzing, by the RIB agent, the route using to make a determination about whether to perform the route action; and performing, by the RIB agent, the route action based on the determination. Route actions may include actions relating to route modification, route redistribution, modifications of various attributes of a route, etc.

Abstract: Embodiments for providing an enhanced codebase in a computing environment by a processor. One or more container specification files may be automatically updated with one or more changes to a codebase.

Abstract: A computer-implemented method for automatically generating a semantic vector representation of a relation between a specific set of entities in natural language text is provided. The method may include, in response to receiving a text segment comprising a set of entities, automatically parsing the text segment into an abstract meaning representation (AMR) graph comprising nodes representing the set of entities. The method may further include extracting a number of minimum Steiner trees from the AMR graph, and wherein each Steiner tree comprises a minimum amount of edges between the nodes corresponding to a first entity and at least one second entity. The method may further include using a trained graph neural network (GNN) to determine vector embeddings for the minimum Steiner trees. The method may further include aggregating the vector embeddings to generate the semantic vector representation of the relation between the specific set of entities.

Abstract: A method, system, and computer program product are disclosed. The method includes receiving an input text and generating a set of virtual triples, which include pairs of named entities from the input text and relation embedding vectors for each of the pairs, from the input text. The method also includes constructing a virtual knowledge graph (KG) with the set of virtual triples and transforming the virtual KG into a relation-cluster KG. Further, the method includes mining logical rules from the relation-cluster KG.

Abstract: The present inventive concept provides for a method for automated decision modelling from text including obtaining a text corpus including a policy. Terms and syntax are identified within the text corpus related to the policy. Sentence similarities and co-references based on the terms and syntax are identified. Discourse and sentence level semantic parsing is performed based on the terms and the sentence similarities and the co-references using machine learning. A decision model template is generated based on the discourse and semantic parsing, and the decision model template is transformed into an automated decision model.

Abstract: Embodiments for providing an enhanced codebase in a computing environment by a processor. One or more container specification files may be automatically generated for a codebase based on one or more extracted attribute names and values.

Abstract: Software that performs the following operations: (i) receiving a set of graph predictions corresponding to an input text, where graph predictions of the set of graph predictions are generated by different respective machine learning models; (ii) blending the graph predictions of the set of graph predictions to generate a plurality of candidate blended graphs, where nodes and edges of the candidate blended graphs have respective selection metric values, generated using a selection metric function, that meet a minimum threshold; and (iii) selecting as an output blended graph a candidate blended graph of the plurality of candidate blended graphs having a highest total combination of selection metric values among the plurality of candidate blended graphs.

Abstract: Various embodiments are provided for correlating regulatory data in a computing environment by a processor. A rule may be associated with one or more textual paragraphs extracted from a policy document that describes at least a portion of the rule.

Abstract: Compositions and methods for the treatment of bacterial infections include conjugates containing an Fc domain covalently linked to one or more monomers of cyclic heptapeptides or one or more dimers of cyclic heptapeptides. In particular, conjugates can be used in the treatment of bacterial infections caused by Gram-negative bacteria.

Abstract: Compositions and methods for the treatment of bacterial infections include conjugates containing an Fc domain covalently linked to one or more monomers of cyclic heptapeptides or one or more dimers of cyclic heptapeptides. In particular, conjugates can be used in the treatment of bacterial infections caused by Gram-negative bacteria.

Abstract: Techniques facilitating automatic feature extraction from a relational database are provided. In an embodiment, a method can include generating an entity graph based on a relational database, wherein the entity graph comprises a first node associated with a first table in the relational database and a second node associated with a second table in the relational database. In another embodiment, the method can include joining the first table and the second table based on an edge between the first table and the second table defined by the entity graph, wherein a resulting joined table is connected by a column of data. In another embodiment, the method can include extracting a feature from the column of data using a data mining algorithm selected from a set of data mining algorithms based on a type of data in the column of data.