306 results about "Entity linking" patented technology

Disclosed herein are various exemplary systems and methods for linking entity references to entities and identifying associations between entities. In particular, a method for identifying an entity from a plurality of entity references, each entity reference being linked with a separate ghost entity, is provided. The method comprises the steps of comparing an entity reference of a first ghost entity with an entity reference of a second ghost entity to determine a match probability between the entity reference of the first ghost entity and the entity reference of the second ghost entity, linking the entity reference of the first ghost entity additionally with the second ghost entity and the entity reference of the second ghost entity additionally with the first ghost entity when the match probability is greater than or equal to a match threshold and repeating the steps of comparing and linking for one or more ghost entity pairings possible from the ghost entities. The method further comprises determining, for one or more entity references linked to a ghost entity, a score for the entity reference based at least in part on a match probability between the entity reference and a value representing the one or more entity references linked to the ghost entity and identifying the ghost entity as an actual entity based at least in part on one or more scores for the one or more entity references linked to the ghost entity.

The invention provides a question and answer method based on a knowledge map. The question and answer method based on a knowledge map provided in the invention is realized by subject entity matching,relationship matching and answer determination. The subject entity matching mainly comprises naming entity identification and entity linking. The naming entity identification is aimed at identifying naming entities such as names of people, names of places, and names of organizations in natural language questions q. The entity linking corresponds the identified naming entity to a certain entity inthe knowledge base, that is, finding out an entity s in triples; Relationship matching is to understand the semantics expressed by question q through natural language understanding technology, and match the relationship p in the triples (s, p, o) in the search space in order to determine the semantics of the question and its corresponding relationship with the knowledge base. The candidate subjectentity is obtained through entity identification and entity linking, and the relationship matching can obtain the candidate relationship, thereby obtaining several candidate triples; the answer determination is to rank the candidate triples according to entity recognition score, relationship match score, etc. to determine the final answer.

The present invention relates to an arrangement, in a communication network system supporting communication of packet data. It comprises / has access to mobile subscriber data and comprises means for handling subscriber identity information. It further comprises service level control means (61,62;6) for allocating service level profiles, e.g. QoS profiles, to subscribers. Said services level control means (61,62;6) comprises profile configuration means, for defining network service level profiles (7) and linking subscriber identity information entities to said network service profiles defining the highest allowed service levels at least for a number of different parameters at least for groups of subscribers identified by said subscriber identity information entities. It optionally comprises first validation means (8A) for validating the service level (profiles) requested by subscribers against operator defined subscriber profiles for said subscribers, and at least second validation means (8B) for validating (validated) subscriber profiles against corresponding defined network service profiles for the requesting subscribers as given by the subscriber identity information entities, such that the resource and / or service level profile allocated to a requesting subscriber (11; 1) can be controlled.

The invention provides an abnormal information text classification method based on a knowledge graph. According to the method, first, a domain knowledge graph is constructed, and an entity identifierand an entity link based on the domain knowledge graph are constructed; second, text feature representation vectors v<text> and entity feature representation vectors v<ent> are constructed; and last,the text feature representation vectors and the entity feature representation vectors are merged to obtain new text representation vectors v<merge> fusing knowledge features, classified training is performed on the new text representation vectors, and a final classification result is obtained.

A method and a system for accessing services provided by network resources in communication networks. Access to service capabilities is controlled at the application level by controlling the access through a gateway wherein an object-oriented service architecture based on abstracted application programming interfaces is implemented. Preferably, the service architecture is defined in OSA / Parlay standards. Access control is carried out by means of a logical entity, the service reference monitor, which is linked to the gateway and configured so that it intercepts all the communications passing between the client applications and the gateway. The service reference monitor captures the object reference to the service capability and assigns to the object reference a lifetime. At the expiration of the lifetime, the service reference monitor destroys the service capability. The probability of a malicious attack is lowered by limiting the time window of the life of access to a service.

A system, method, and mobile device application are configured to capture, with a mobile device, a document such as a next generation sequencing (NGS) report that includes NGS medical information about a genetically sequenced patient. At least some of the information is extracted from the document using an entity linking engine, and the extracted information is provided into a structured data repository where it is accessible to provide information regarding the patient specifically as well as collectively as part of a cohort of patients with similar genetic variants, medical histories, or other commonalities. In one aspect, the document is matched to a template model, and the document is processed using one or more masks segregating the template model, and therefore the document, into a series of distinct subregions.

The invention discloses an information retrieval-based question and answer system and method for knowledge graph energization, which integrally improve the question and answer effect of the system, expand the user consultation range and improve the question feedback accuracy. According to the technical scheme, the system comprises a knowledge map database for storing domain knowledge map information; a word segmentation and part-of-speech tagging module which segments the user questions and tags the part-of-speech of the user questions; an entity identification and link module which identifiesentities in the user questions and links the entities to nodes in the knowledge graph database; an intention understanding module which obtains an intention understanding result of the user problem based on the entity link result and the distributed representation vector; a retrieval module which retrieves a plurality of corresponding question and answer pairs as roughing results according to theinformation in the user questions based on the retrieval data source; a sorting module which is used for resorting the roughing results by utilizing the distributed representation vectors of the entities; and a semantic matching module which scores the reordering result by using the distributed representation vector of the entity and finally outputs an answer.

The invention discloses a method and a system for linking entities. The method includes acquiring to-be-linked entities from given texts; acquiring entity names and abbreviation word banks from preset knowledge bases and establishing synonym banks of the entity names on the basis of the preset knowledge bases; carrying out searching in the synonym banks by the aid of entity keywords; linking the entity keywords for searching and the entity names in the preset knowledge bases if a certain entry matched with the synonym banks is found by means of searching; generating candidate entities if the certain entry is not found by means of matching and carrying out disambiguation linking in context similarity evaluation modes. The synonym banks contain the entity names acquired from the preset knowledge bases and information data related to the entity names. The entity keywords are acquired by means of word segmentation and are used as search terms. The entity names in the knowledge bases correspond to the entry. The method and the system in an embodiment of the invention have the advantage that the entity linking accuracy can be improved.

The invention discloses a multi-strategy fusion knowledge question and answer method and system, and the method comprises an offline part and an online part, the offline part is mainly used for data preparation and model training, and the online part is mainly used for system service, and the method comprises the steps: receiving a statement input by a user, and correcting a spelling error; Performing word segmentation and part-of-speech tagging on the statement input by the user; Extracting entity information in the user statement, and linking the entity to the knowledge graph node; Obtainingan executable query statement through a multi-strategy fusion semantic analysis step according to the result of the entity recognition and connection process; Executing a query on a knowledge graph by the executable query statement to obtain an answer, and then generating a corresponding natural language reply user according to the answer through a reply generation mode combined by multiple methods, so that the question and answer system is suitable for question query of general and domain knowledge graphs, the system robustness is improved, and meanwhile, the good interpretability and controllability are achieved.

A system for linking entities associated with electronic transactions that are monitored for compliance with predetermined compliance policies of an enterprise. The system allows establishment, codification, and maintenance of enterprise policies, monitors electronic transactions of the enterprise from various data sources, detects exceptions to established policies, reports exceptions to authorized users such as managers and auditors, and / or provides a case management system for tracking exceptions and their underlying transactions. A monitoring database stores data corresponding to monitored transactions and support entities. A transactions analysis engine executes computer-executable compliance policy statements against the monitoring database to determine whether a transaction has indicated an exception to a policy. The transaction analysis engine retrieves information corresponding to a particular prestored support entity that causes an exception. Information is retrieved corresponding to other support entities that are related to the particular prestored support entity, so as to link related transactional entities.

The invention discloses a construction method of a knowledge graph library for network fault analysis and application thereof, and relates to the technical field of network communication. The method comprises: using an intelligent method to carry out data acquisition on communication network data; constructing ontology libraries in different fields, constructing a global ontology library by adopting a data fusion and mapping technology according to the ontology libraries in different fields, and finally constructing a knowledge map library with consistent semantic relationships of various datasources through entity alignment, entity linking and knowledge calculation in sequence. The constructed knowledge graph library is used for retrieving possible reasons for causing the network fault,suggestions of a fault solution are provided for a user, rapid positioning and solution of the network fault are facilitated, the fault processing efficiency is improved, and meanwhile the influence of human factors is reduced.

The invention discloses a Web-based domain knowledge map construction system and method. The system comprises a knowledge modeling subsystem, a data and entity link subsystem, a human assisted labeling subsystem and a knowledge visualization subsystem, wherein the knowledge modeling subsystem is sued for obtaining an original knowledge model according to a preset data resource, and receiving an operation instruction of an operation interface so as to construct a data mode of a knowledge map to obtain a knowledge model; the data and entity link subsystem is used for extracting knowledges according to multiple types of data and storing the extracted knowledges into the knowledge map; the human assisted labeling subsystem is used for receiving a user labeling instruction so as to change the knowledge map according to the user labeling instruction; and the knowledge visualization subsystem is used for visually displaying the knowledge model, a dynamic link between the knowledge model and an entity and the changed knowledge map. The system is capable of simply and conveniently completing the work such as knowledge modeling, knowledge obtaining and knowledge visualization, so that the domain knowledge map construction difficulty is greatly reduced and benefit is brought to enhance the accuracy of domain knowledge maps.

The present teaching relates to entity linking. In one example, a text string is received. The text string is segmented to obtain a segmentation with a set of one or more segments of the text string. A set of entities are identified, with respect to the one or more segments, from a plurality of entities as linked to the one or more segments. The identifying is in accordance with a probabilistic model based on surface form information associated with the plurality of entities.

There are provided measures for centralized IP address management for distributed gateways. Such measures exemplarily comprise management of IP addresses for hosts being linked with a plurality of distributed gateway entities via a first host-specific tunnel at a centralized controller entity, and control of the plurality of distributed gateway entities in terms of Internet protocol address management from the centralized controller entity via a second host-specific tunnel on the basis of the managed Internet protocol addresses for the hosts. Accordingly, control-plane and user-plane functions may be separated between the centralized controller entity and the plurality of distributed gateway entities.

The invention discloses a method and a system for linking entities. The method comprises: pre-processing input texts and a knowledge base, obtaining mentions and contexts thereof, and entity keywords; retrieving candidate entities of each mention; classifying the mentions in two kinds according to the number of candidate entities of the mentions, the mentions whose number of candidate entities is smaller than a preset threshold being clear-cut mentions, and others being undefined mentions; performing first stage entity linking on the clear-cut mentions; through similarity of the mentions and the entities in the knowledge base, and similarity among the entities, using a method of a corresponding relation graph of a preset mention and the entities to complete screening of the candidate entities; and according to linked target entities, performing second stage linking on the undefined mentions. The method respectively performs calculation of entity linking in stages according to whether the mentions are the clear-cut mentions or not, so that complexity of the algorithm is greatly reduced. Through upgrading the contexts of the mentions, for example, the linked entities, entity linking can be performed on the mentions in a text more accurately and rapidly.

The invention relates to a domain event graph construction method and device fusing multiple types of facts and entity knowledge. The method comprises the following steps: performing cause relationship extraction and instance cause element extraction on a domain corpus to form an instance cause logic knowledge base; constructing an abstract concept knowledge base with hierarchy; performing entityword abstraction and predicate abstraction on instance events in the instance cause logic knowledge base by utilizing the abstract concept knowledge base to form an abstract cause graph; carrying outentity linking on instance events in the instance cause logic knowledge base by utilizing the entity knowledge graph and adopting an entity linking technology, and fusing event knowledge and entity knowledge to form a cause knowledge graph; and combining the abstract factorial map with the factorial knowledge map to form a domain event map. The advantages of static entity knowledge and action event knowledge can be integrated, the application range of knowledge questions and answers can be widened, and the domain event graph can be used as a common knowledge base to expand domain language resources.

The invention provides a relation extension method based on entity links. The method is characterized in that the technological means of entity links are used, text in natural language is linked to the corresponding entities in knowledge bases, unlabeled entities in message box attributes are identified, using the labeling systems of encyclopedic entries to serve as the types of the entities according to the matching degree between candidate entity types and entity types at two ends of a relation; meanwhile, a model fusion method is used to sort the candidate entities, and the advantages of a nonlinear boosting integrated model are fused into a linear model so as to increase model performance and guarantee relation accuracy. By the method, unlinked entities in the message box can be identified effectively, the problems of entities with identical names and entities with aliases are solved, a relation with the target entity is built, and relation extension is achieved.

A method and system for administering software product installation, removal and updating on a computer network according to a versioning database, including loading a software distribution set into a versioning database, the software distribution set comprising a software product having a plurality of files for operating the software product on a computer. Loading includes loading a first entity identifying the software distribution set into the versioning database, determining whether an identity of each of the plurality of files is currently identified as an entity currently provided on the versioning database, loading a plurality of second entities each corresponding to a respective file of the plurality of files, wherein only those files of the plurality of files determined not to be identified as an entity currently provided on the versioning database are loaded as second entities. The method and system further include storing the plurality of files, linking the first entity with the plurality of second entities, targeting a workstation in communication with the computer network for installation of the software product corresponding to the software distribution set and installing the software product on the targeted workstation.

The invention discloses an entity linking method based on deep learning, which comprises the following steps: obtaining entity reference to be linked in a document to be identified, and extracting a candidate entity set corresponding to the entity reference in a library; calculating the conceptual similarity between each candidate entity and entity reference, and extracting the candidate entity with the highest conceptual similarity to entity reference from the candidate entity set as the entity to be linked; obtaining attribute information of the entity to be linked, judging whether the entity to be linked can be linked with the corresponding entity reference, and linking the entity to be linked that can be linked with the entity reference. The method can judge whether the candidate entity can be linked with the entity reference by combining the attribute information of the candidate entity and the concept similarity, the conceptual similarity between candidate entity and entity reference is determined, whether the candidate entity links the two processes of entity reference to carry out joint modeling, and whether the candidate entity can link with entity reference automaticallyin the process of model training, so as to make the judgment more accurate.

The invention discloses a question and answer method and device based on a knowledge graph, electronic equipment and a storage medium. The question and answer method based on knowledge graph comprisesthe steps of obtaining a question sentence in response to a triggered user input request; performing entity linking on the entities in the questions obtained through named entity identification in aconstructed knowledge graph to obtain candidate entities; determining a search subgraph containing the candidate entities in the knowledge graph, and generating a plurality of candidate paths pointingto candidate answers by the candidate entities according to the search subgraph; and according to the context information of the question sentence, screening from the plurality of candidate paths toobtain a target path, and pushing a candidate answer pointed by the candidate entity in the target path as an answer of the question sentence to the user. By adopting the knowledge graph-based question and answer method and device, the electronic equipment and the storage medium provided by the invention, the problem of low accuracy of knowledge graph-based question and answer in the prior art issolved.

The present invention discloses an entity linkage algorithm based on a graph model. The entity linkage algorithm based on a graph model is characterized by comprising: forming a candidate entity by using the Wikipedia knowledge base; constructing a semantic feature between the entities by using LDA; constructing relationships between entities based on linkage structures of Wikipedia to form a graph model; and integrating related semantic features into the graph model; and ranking the entities by using the PageRank algorithm to obtain an entity linkage result, which specifically comprises steps of calculation and integration of a naming dictionary, a candidate entity set, related features, construction of the graph model, and ranking of candidate entities. Compared with the prior art, the entity linkage algorithm based on a graph model has the advantages of being good in entity feature integration and high in reliability of the entity linkage result; data is downloaded by using Wikipedia, so that no additional costs are needed, and especially data sets do not need to be noted manually; and the method is simple, convenient in usage, and saves time and efforts.

The present invention discloses a Chinese integrated entity linking method based on a graph model. An ambiguous entity in a text can be mapped into a specific entity in a real world, in order to provide aid for knowledge base expansion, information extraction and search engines. The method mainly comprises three parts of generating a candidate entity, constructing an entity indicator diagram, and disambiguating an integrated entity. For a given text, an entity referent item therein is recognized to obtain the candidate entity. The entity referent item and the candidate entity thereof are regarded as graph nodes to construct an entity referent graph. An in-degree and out-degree algorithm is applied to the entity indicator diagram for implementing disambiguation of multiple ambiguous entities in the text. The present invention does not depend on the knowledge base completely in the establishment of the entity indicator diagram, and also can implement incremental evidence mining to find evidence on an encyclopedia webpage. Dependence path analysis is employed to find the possibly related entity referent item. When the dependence path sizes of two entity referent items are within a set range, the two entity referent items are regarded as the possibly related entity referent items. Further, whether their candidate entities have relations in the real world is determined, so that the efficiency of disambiguation is greatly improved.

The invention relates to an entity link system for a language lacking resources. The system adopts a method combining rules with statistics for carrying out word stem segmentation and part-of-speech tagging on Uygur language vocabularies; expanding entity referring items according to contexts of the entity referring items; aligning Chinese vocabularies with the Uygur language vocabularies by means of the bilingual alignment technology of machine translation, so as to expand the Uygur language via the abundant semantics of the Chinese and obtain candidate entities; sequencing the candidate entities by fusing entity context features, textual theme features and concept map features in a knowledge base, and linking the entity referring items to the sequenced target entities. The system provided by the invention is used for solving the entity link problem of the language lacking resources and creating a practical Uygur language entity link system. The system can achieve an entity link function of the Uygur language lacking language resources so as to satisfy the demand of intelligent information processing.

The invention discloses a semantic parsing method and a device, electronic equipment and a storage medium, and relates to the technical field of electronic equipment. The method comprises the following steps of: obtaining a to-be-queried statement, performing entity identification on the to-be-queried statement, obtaining a target entity in the to-be-queried statement, performing entity linking onthe target entity and the knowledge graph to obtain entity content corresponding to the target entity, and performing intention analysis on the to-be-queried statement based on the entity content toobtain at least one intention category corresponding to the to-be-queried statement. According to the semantic parsing method and the device, the electronic equipment and the storage medium, the entity content corresponding to the target entity is obtained from the knowledge graph through the entity link, and then intention analysis is performed on the entity content to obtain at least one intention classification, so that the problem of recall is solved, and the effect of supporting media vertical domain knowledge questions and answers is achieved.

A method and a system for determining taxes attributable to a financial transaction create a tax rate table, link an entity of the financial transaction to the tax rate table through a product rule, and calculate taxes based on the tax rate table according to one component of the financial transaction. The tax rate tables can be linked by a default product rule, which is a defined by a global variable. Alternatively, specific product rules can be used to link specific entities, such as tax jurisdiction records, or legal entity records. In one application, the method and the system calculate revenue tax, cost tax, input tax, and profits for each transaction. The method and the system may further include multi-currency support analysis for a financial transaction so that a financial transaction can be analyzed under a common currency, even though the financial transaction is conducted using one or more currencies in one or more jurisdictions.

The invention relates to the field of artificial intelligence, discloses a medical field intention recognition method, device and equipment and a storage medium, is applied to the field of smart medical treatment, and improves the accuracy of a medical field intention recognition result. The method comprises the steps of obtaining an initial question statement from a terminal; calling a preset identification model to perform entity identification on the initial question statement to obtain an entity identification result; performing entity linking on the plurality of coarse-grained entity tagsaccording to a preset medical entity synonym table to obtain linked entity tags; performing intention recognition on the initial problem statement according to a preset intention recognition model, an entity recognition result and the linked entity label to obtain candidate medical intentions; generating knowledge graph query statements according to the candidate medical intentions; and performing knowledge graph query in a preset medical knowledge graph based on the knowledge graph query statement to obtain a knowledge graph query result, generating a corresponding target verbal skill according to the knowledge graph query result, and sending the target verbal skill to the terminal.

The invention discloses an end-to-end context-based knowledge base question and answer method and device, and the method and device consider the connection relationship between entities and relationships in a knowledge base, enable the two tasks including entity links and relationship prediction contained in the knowledge base to be mutually promoted, and jointly improve the two tasks. The methodmainly comprises the steps of prreprocessing a problem and removing special symbols; constructing a candidate entity set related to the problem based on the knowledge base, and constructing a candidate relationship set according to the relationship of the candidate entities in the knowledge base; for each entity in each candidate set, extracting the context of the entity in the question; dividingthe candidate relationships into different granularities; predicting a subject entity and a predicate relationship based on the CERM model; and finding the object entity in the knowledge base as an answer to return by using a predicted subject entity and relationship. Entity links and relationship prediction in knowledge base questions and answers are integrated into a unified prediction model. Joint prediction of the subjective entities and relationships is achieved, and accuracy of questions and answers is improved.