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6690 results about "Knowledge graph" patented technology

A Knowledge Graph is a model of a knowledge domain created by subject-matter experts with the help of intelligent machine learning algorithms.

Question and answer method based on knowledge graph, and agricultural encyclopedia question and answer system

The invention provides a question and answer method based on a knowledge graph, and an agricultural encyclopedia question and answer system. A natural language question raised by a user can be automatically analyzed; a topological structure based on a syntax tree is formed; retrieval and comparison are carried out through the topological structure and a question template in a grammar library; according to a mapping relation between the topological structure and a predicate nominatum, and a mapping relation between a synonym set and a relation or an attribute in the knowledge graph, a question-mapped predicate is obtained; in combination with an entity identified in the question, a final structured knowledge graph query statement is generated; retrieval is carried out in the knowledge graphaccording to the query statement; and a final result is returned. When the relevant topological structure cannot be retrieved in a question template library, the question answering is carried out bycalling common question-answer pairs of an FAQ question library. The question and answer system can give accurate answer retrieval for the question posed by the user, so that the satisfaction degree of the user to the agricultural encyclopedia question retrieval is improved.
Owner:南京柯基数据科技有限公司

Method and device for acquiring knowledge graph vectoring expression

ActiveCN105824802ARich relevant informationSolve the problem of insufficient representation effect caused by sparsityNatural language data processingSpecial data processing applicationsStochastic gradient descentGraph spectra
The invention discloses a method and a device for acquiring knowledge graph vectoring expression. The method comprises the following steps of labeling an entity, existed in and belonging to a knowledge graph, in a given auxiliary text corpus by utilization of an entity labeling tool according to a to-be-processed knowledge graph so as to obtain an entity-labeled text corpus; constructing a co-occurrence network comprising words and entities on the basis of the text corpus so as to relate text information of the auxiliary text corpus to entity information of the knowledge graph, and then learning to obtain a text context embedded expression; respectively modeling the embedded expression of the entity and relation in the knowledge graph according to the text context embedded expression so as to obtain an embedded expression model of the knowledge graph; training the embedded expression model by utilization of a stochastic gradient descent algorithm so as to obtain the embedded expression of the entity and relation in the knowledge graph. The method and the device disclosed by the invention have the advantages that not only can the expression capability of the relation be improved, but also the problem of insufficient expression effect caused by sparseness of the knowledge graph can be effectively solved.
Owner:TSINGHUA UNIV

Knowledge graph-based interactive question and answer method and system

The invention discloses a knowledge graph-based interactive question and answer method and system. The method comprises the steps of constructing a knowledge graph, wherein data in the knowledge graphis from multiple open-source information sources; according to existing entities in the knowledge graph, forming a dictionary, forming mapping from a name to a professional field through a manual tagging method, and performing expansion in a conventional feature modeling mode to form a professional dictionary; according to the data in the knowledge graph, forming mapping from the entities to a training set of the field through the manual tagging method to establish a classifier; according to the professional dictionary, performing word segmentation on a natural question sentence through a forward maximum matching method, and according to results after word segmentation, inputting the results to the classifier for performing classification, thereby classifying the natural question sentenceinto questions in different fields; and mapping the classified questions to obtain corresponding question templates, and converting the question templates into query sub-graphs in the knowledge graph. Answer can be performed for sentences of more complex questions, so that the answer quality can be ensured and the manual intervention is effectively reduced.
Owner:HUAZHONG UNIV OF SCI & TECH

Knowledge graph management method and system based on semantic space mapping

The invention belongs to the technical field of text semantic processing and semantic webs, and particularly relates to a knowledge graph management method and system based on semantic space mapping. The method comprises the steps of semantic vector construction, semantic space mapping and knowledge graph management, wherein the step of knowledge graph management comprises three sub-steps of semantic clustering, semantic duplication eliminating and semantic annotation. A text unit describing edge / nodal points of a knowledge graph is projected to a semantic space, and vector representation of the edge / nodal points on the semantic space is obtained by vector accumulation; on the basis, multiple management tasks of the knowledge graph are achieved. The system correspondingly comprises a semantic vector construction module, a semantic space mapping module and a knowledge graph management module. The defects that a conventional knowledge graph management method is sensitive to factors such as word deformation, synonym variation and grammatical form variation are overcome, the situation of difference of the number of words can be easily handled in a vector accumulation mode, and further knowledge graph management tasks such as semantic clustering, semantic duplication eliminating and semantic annotation are easily achieved.
Owner:FUDAN UNIV
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