Word2vec medical similar question retrieval method based on improved tf-idf weighting
A problem and medical technology, applied in the field of word2vec medical similar problem retrieval, can solve the problems of mixed medical information, proper noun identification and modeling difficulties, etc., to improve user experience, identify clear, and solve the effects of identification and modeling difficulties.
Pending Publication Date: 2021-12-31
BEIJING INST OF COMP TECH & APPL
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[0008] The technical problem to be solved by the present invention is how to provide a word2vec medical similarity question retrieval method based on improved tf-idf weighting to solve the problem of returning the user's desired result based on the existing medical question and answer data after receiving the user's inquiry ; Difficulties in identifying and modeling proper nouns and mixed medical information
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[0038] In order to make the purpose, content and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.
[0039] In view of the above problems, this patent proposes a word2vec medical similarity retrieval method based on improved tf-idf weighting. Firstly, a database of medical question-and-answer pairs is established. After the user asks a question, it searches specifically for questions in the medical field, and finally returns a question-answer pair with a high degree of similarity to the user's question as the output of the search result.
[0040] Strengthen the attention to proper nouns while searching. Using TF-IDF, weights are added to all words, indicating the importance of words and their impact on the calculation of the similarity of the entire sentence. For words that need to be emphasized, such as proper nouns,...
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The invention relates to a word2vec medical similar question retrieval method based on improved tf-idf weighting, and belongs to the field of online medical treatment. The method comprises: firstly, constructing a medical question and answer pair database, and performing retrieval answering through medical question and answer pairs in the database in subsequent retrieval; performing data preprocessing on data in the database and a user question, separately calculating an improved tf-idf value of each lexical item in a user input and a medical question pair, performing word embedding, and multiplying a word2vec word vector of each word by the tf-idf value to obtain a final text vector, such that the analysis of the user question and the database is completed to be used as the basis of subsequent retrieval; and finally, according to the analyzed data, by calculating the similarity between the questions, finding out semantically related questions from the question and answer pair database, and returning the questions with relatively high similarity. According to the method, the problem that proper nouns are difficult to recognize and model is solved, the problem that medical information is mixed is solved, and the user experience is greatly improved.
Description
technical field [0001] The invention belongs to the field of online medical treatment, and in particular relates to a word2vec medical similar question retrieval method based on improved tf-idf weighting. Background technique [0002] Today, with the widespread use of the Internet, it has become the norm to obtain medical knowledge through retrieval. However, due to unknown sources of knowledge and mixed medical information, traditional search engines do not meet the medical needs of users. The question answering system recognizes the user's questioning intention and returns the answer the user wants, such as Ali's butler "Xiaomi", Baidu's Xiaodu, Huawei's Xiaoyi, etc. Automatic question answering systems have been applied to a wide range of fields. Therefore, it has become an urgent need to automatically reply to users' questions based on existing medical question-and-answer data. [0003] Wong et al designed the enquireMe system by building a knowledge base of medical qu...
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IPC IPC(8): G06F16/332G06F16/33G06F40/284G16H50/70
CPCG06F16/3329G06F16/3335G06F40/284G16H50/70
Inventor刘洋张宁雨孙渊博
OwnerBEIJING INST OF COMP TECH & APPL