This type of data application is the semantic consumption scene, including natural language retrieval, intelligent analysis, knowledge reasoning, etc. The core is to use the knowledge in the graph through rules or deep learning to form a certain artificial intelligence. The job function email list above is an analysis of the application of knowledge graphs from the perspective of technical application, but all knowledge graphs ultimately form products and provide services. job function email list From the various products we have come into contact with, it can be divided into general knowledge graphs, vertical domain knowledge graphs,
As well as components and standardized, process-based, and job function email list automated tools that provide services for enterprises and specifically build knowledge graphs. The general knowledge graph is our common search engine, question answering system, or various encyclopedias. Since Google released the knowledge graph project in 2012 and announced the construction of the next-generation intelligent search engine based on this, the application job function email list of knowledge graphs has gradually deepened. Now using Google, Baidu, etc. to search, it is no longer just keyword matching, but keyword-enhanced retrieval, that is, a set of synonyms,
Hyponyms and other words in the map of the job function email list search term to search together to expand or constrain the search . At the same time, job function email list more ontologies and instances can be associated to directly find the answer or show all the relationships related to the search terms. For example, if you search for a certain movie, you can see all the main actors, directors, release dates and other information of the movie in the form of a map. Regarding relational search and structured display, a more intuitive example is Tianyancha. You can search for a company to find all its affiliated subsidiaries and legal persons, etc.,