Abstract: Safety geofence zones may be created and deployed for a ride sharing service. At least one set of safety geofence zones may be created which are associated with a ride sharing service. A zone type may be set for each set of safety geofence zones in the at least one set of safety geofence zones. At least one trigger condition may be set for the at least one set of safety geofence zones. The at least one set of safety geofence zones may be deployed.

Abstract: Dynamic geofence zones may be deployed and updated for a ride sharing service. At least one set of dynamic geofence zones may be created which are associated with a ride sharing service. At least one time period may be set for the at least one set of dynamic geofence zones. The at least one set of dynamic geofence zones may be deployed. The at least one set of dynamic geofence zones may be updated.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.

Abstract: Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.

Abstract: Process states of computing devices may be obtained and processed. Process event information of a computing device may be obtained. The process event information may characterize states of processes of the computing device. The process event information may be stored within a queue. Graph information may be determined based on the process event information within the queue. The graph information may characterize states of processes of the computing device using nodes and edges. The graph information may be stored within a graph database.

Abstract: Process states of computing devices may be collected for processing. Process event information of a first computing device may be determined based on an observation of process creation events and process termination events, a garbage collection, and a process scan. The process event information may be provided to a second computing device.

Abstract: Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.

Abstract: Methods, systems, and computer program products for constraint tracking and inference generation are provided herein. A computer-implemented method includes parsing descriptions of one or more user-provided constraints pertaining to data within a target system, parsing truth value assignments to the user-provided constraints, and deriving a truth value for at least one of the user-provided constraints that does not correspond to a known truth value, wherein said deriving comprises performing a logical inference utilizing known truth values of one or more of the user-provided constraints. The computer-implemented method also includes storing, in a database, (i) the user-provided constraints, (ii) the known truth values, and (iii) the at least one derived truth value, and outputting the at least one derived truth value, one or more identified contradictions among the known truth values, and/or an indication that one or more unknown truth values corresponding to the user-provided constraints remain unknown.

Abstract: Process states of computing devices may be obtained and processed. Process event information of a computing device may be obtained. The process event information may characterize states of processes of the computing device. The process event information may be stored within a queue. Graph information may be determined based on the process event information within the queue. The graph information may characterize states of processes of the computing device using nodes and edges. The graph information may be stored within a graph database.

Abstract: Process states of computing devices may be collected for processing. Process event information of a first computing device may be determined based on an observation of process creation events and process termination events, a garbage collection, and a process scan. The process event information may be provided to a second computing device.

Abstract: A training query generation system is usable to generate fully formed training questions from prior search queries, some of which may be fully formed search queries and some of which are not fully formed. The system may identify fully formed questions from a query database stored on a storage device. The query database includes a plurality of search query character string, The system further identifies partially formed questions from the query database, creates question templates from the identified fully formed questions, and stores the question templates in a template database. The system then identifies entities with the partially formed questions, classifies each entity, and stores the classified entities in an entity database. Fully formed questions can then be generated using the question templates from the template database and classified entities from the entity database.

Abstract: A training query generation system is usable to generate fully formed training questions from prior search queries, some of which may be fully formed search queries and some of which are not fully formed. The system may identify fully formed questions from a query database stored on a storage device. The query database includes a plurality of search query character string, The system further identifies partially formed questions from the query database, creates question templates from the identified fully formed questions, and stores the question templates in a template database. The system then identifies entities with the partially formed questions, classifies each entity, and stores the classified entities in an entity database. Fully formed questions can then be generated using the question templates from the template database and classified entities from the entity database.

Abstract: A training query generation system is usable to generate fully formed training questions from prior search queries, The system may include a training dataset generation service that is configured to receive a message containing an indicator of a topic over a network, access a template database containing a plurality of question templates and associated topic indicators, each question template including one or more argument values indicative of a role, and select those question templates from the template database that match the received topic indicator. The training dataset generation service also is configured to select entities from an entity database that map to the argument values of the selected question templates and generate a plurality of fully formed questions, each generated fully formed question comprising a character string containing the question template and at least one of the selected agents.

Abstract: One embodiment provides method for constructing a cross-lingual information extraction program, the method including: utilizing at least one processor to execute computer code that performs the steps of: constructing a plurality of language-specific representations from text expressed in a plurality of languages by parsing the text of each language using a language-specific semantic parser; mapping the plurality of language-specific representations to a single cross-lingual semantic representation, wherein the cross-lingual semantic representation encompasses the plurality of languages; and constructing the cross-lingual information extraction program based on the cross-lingual semantic representation. Other aspects are described and claimed.

Abstract: An FPGA clock signal self-detection method relates to the technical field of control module, and the technical problem to be solved is to improve operational reliability and safety of the FPGA chip. The method comprises introducing two clock signals to an FPGA chip, wherein one clock signal is a first clock signal, and the other clock signal is a second clock signal; using the first clock signal to control all synchronous logic operations in the FPGA chip, and using the second clock signal to detect the first clock signal for correctness. The method of the invention is particularly applicable to a system with the FPGA chip as a main controller or important control unit.

Abstract: One embodiment provides a method for generating a natural language resource using a parallel corpus, the method including: utilizing at least one processor to execute computer code that performs the steps of: receiving, from a parallel corpus, natural language text in a source language and a corresponding translation of the natural language text in a target language, wherein the natural language text in the source language comprises linguistic annotations; projecting the linguistic annotations from the source language natural language text to the target language natural language text; applying one or more filters to remove at least one projected linguistic annotation from the target language natural language text that results in at least one error; selecting at least one target language natural language text having substantially complete linguistic annotations; training a machine learning model using the selected at least one target language natural language text and annotations; and adding, using the trained

Abstract: One embodiment provides method for constructing a cross-lingual information extraction program, the method including: utilizing at least one processor to execute computer code that performs the steps of: constructing a plurality of language-specific representations from text expressed in a plurality of languages by parsing the text of each language using a language-specific semantic parser; mapping the plurality of language-specific representations to a single cross-lingual semantic representation, wherein the cross-lingual semantic representation encompasses the plurality of languages; and constructing the cross-lingual information extraction program based on the cross-lingual semantic representation. Other aspects are described and claimed.

Abstract: One embodiment provides a method for generating a natural language resource using a parallel corpus, the method including: utilizing at least one processor to execute computer code that performs the steps of: receiving, from a parallel corpus, natural language text in a source language and a corresponding translation of the natural language text in a target language, wherein the natural language text in the source language comprises linguistic annotations; projecting the linguistic annotations from the source language natural language text to the target language natural language text; applying one or more filters to remove at least one projected linguistic annotation from the target language natural language text that results in at least one error; selecting at least one target language natural language text having substantially complete linguistic annotations; training a machine learning model using the selected at least one target language natural language text and annotations; and adding, using the trained

Abstract: Search results are provided for a search query. A search query including an entity and entity type is received. The entity is parsed into semantic components. Variants are generated based on input from auxiliary information and user configuration information for each of the semantic components. The entity is recomposed in different morphological forms from different variants of the semantic components. At least one morphological form for the entity is presented as a search result.