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Knowledge system-based knowledge graph model creation method and graph retrieval method
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A technology of knowledge map and system, which is applied in the field of map retrieval and knowledge map model creation, and can solve problems such as inability to map, heavy workload, and large amount of calculation
Pending Publication Date: 2020-12-18
HANGZHOU FANEWS TECH
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[0002] In many current search services, clustering algorithms are usually used to iteratively calculate specified data to retrieve topics, but the computational complexity of iterative calculations through clustering algorithms is high, and the amount of calculation is large, which leads to the speed of retrieving topics Often it takes hours or even days
However, the maps of various industries in the public system are not applicable to all data, and the workload of drawing different maps is huge; and all maps cannot be intuitively felt by users
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Embodiment 1
[0061] First, search for the created keyword, and perform semantic expansion on the created keyword according to the first search result, so as to obtain associated phrases corresponding to each created keyword;
[0062] Subsequently, the weight of each associated word is obtained in the associated phrase group, and the associated words of the first preset number are recorded as preset core words from top to bottom according to the order of weight;
[0063] Next, set the node relationship between the preset core word and the creation keyword according to the semantic relationship between the preset core word and the creation keyword;
[0064] Then, write the created keywords and the preset core words into the knowledge graph model directly according to the node relationship between the created keywords and the preset core words;
[0065] Next, set the preset core words as keywords to execute the above steps, that is, perform semantic expansion on the preset core words accordin...
Embodiment 2
[0070] First, search for the created keyword, and perform semantic expansion on the created keyword according to the first search result, so as to obtain associated phrases corresponding to each created keyword;
[0071] Subsequently, the weight of each associated word is obtained in the associated phrase group, and the associated words of the first preset number are recorded as preset core words from top to bottom according to the order of weight;
[0072] Next, set the node relationship between the preset core word and the creation keyword according to the semantic relationship between the preset core word and the creation keyword;
[0073] Next, set the preset core words as keywords to execute the above steps, that is, perform semantic expansion on the preset core words according to the first search result, so as to obtain secondary core words associated with the preset core words;
[0074] Next, calculate the weight of the secondary core words, and screen the secondary cor...
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Abstract
The invention provides a knowledge system-based knowledge graph model creation method and a graph retrieval method, and the creation method comprises the steps: searching a creation keyword, and carrying out the semantic extension of the creation keyword according to a first search result in combination with the field where the creation keyword is located, so as to obtain an associated word groupcorresponding to each creation keyword; obtaining the weight of each associated word in the associated word group, and sequentially marking a preset number of associated words as preset core words from top to bottom according to the sequence of the weights; and setting a node relationship between the preset core word and the creation keyword according to the semantic relationship between the preset core word and the creation keyword, and writing the creation keyword and the preset core word into the knowledge graph model according to the node relationship between the creation keyword and the preset core word. The method has the beneficial effects that the associated phrases associated with the creation keywords needing to be inquired are intuitively inquired in the knowledge graph model, and the weights of the associated words are consulted in the associated phrases.
Description
technical field [0001] The invention relates to the technical field of information retrieval, in particular to a method for creating a knowledge graph model based on a knowledge system and a graph retrieval method. Background technique [0002] In many current search services, clustering algorithms are usually used to iteratively calculate specified data to retrieve topics, but the computational complexity of iterative calculations through clustering algorithms is high, and the amount of calculation is large, which leads to the speed of retrieving topics It often takes hours or even days to wait. However, the maps of various industries in the public system are not applicable to all data, and the workload of drawing different maps is huge; and all maps cannot be intuitively felt by users. [0003] Therefore, there is currently a need for a knowledge graph model that is applied to all industry graphs; and a suitable search method combined with the knowledge graph model is use...
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