Scientific and technological resource matching method based on Pagerank algorithm
A technology of resource matching and technology, applied in the field of search engines, can solve problems such as unreasonable document sorting, and achieve the effect of increasing fairness, ensuring accuracy, and ensuring quality
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Embodiment 1
[0039] In this example, see Figure 1-Figure 2 , a technology resource matching method based on the Pagerank algorithm, comprising the following steps:
[0040] Step 1: Use the Spring framework of IDEA software to build a basic Elasticsearch search engine;
[0041] Step 2: Use the Elasticsearch search engine to crawl and parse the paper data from the resource pool, and put it into the Elasticsearch index library;
[0042] Step 3: Define a new document value sorting algorithm based on the Pagerank sorting algorithm, and combine the Elasticsearch correlation, calculate and modify to obtain a new correlation score calculation rule;
[0043] Step 4: Query according to the input keywords. When generating a Request in IDAE, use the newly defined correlation scoring rules to sort the document value according to the score.
[0044] This embodiment is based on the matching method of scientific and technological resources based on the Pagerank algorithm, starting from the document res...
Embodiment 2
[0046] This embodiment is basically the same as Embodiment 1, especially in that:
[0047] In this example, see Figure 1-Figure 3 , use the Elasticsearch-head-master plugin to visualize the Elasticsearch index library.
[0048] In this embodiment, in step 1, the Elasticsearch version is configured in the configuration file of the Spring project, and the data search is realized by calling the SearchRequest, SearchResponse, RestHighLevelClient, and TermQueryBuilder APIs in Elasticsearch.
[0049] In this embodiment, in step 2, build a Spring project based on the Spring project framework in IDEA, pay attention to the Elasticsearch search engine version bound to the project in the pom.xml file, and bind maven to the Elasticsearch search engine The 3.6.3 version of the 3.6.3 version automatically imports the required jar package. After the project is built, and after obtaining the permission of the resource platform, use a simple crawler to crawl the resource data of the paper an...
Embodiment 3
[0064] This embodiment is basically the same as the above-mentioned embodiment, and the special features are:
[0065] In this example, if figure 1 Shown: borrow IDEA software to build a Spring project, use Elasticsearch (7.6.1) to build a search engine, use IKAnalyzer for the tokenizer, and combine the Elasticsearch-head-master plug-in to realize the visualization of the Elasticsearch index library, such as image 3 shown.
[0066] Such as figure 2 As shown: since the query object is a scientific paper document, the present invention mainly modifies the correlation calculation method of Elasticsearch, and adds the value attribute of the scientific paper document. For the value score of scientific and technological papers, a new formula is proposed to calculate the score, and it is gradually realized according to steps 3.1 to 3.5. The details of the steps are as follows:
[0067] Step 3.1: The inherent value of scientific papers is mainly determined by the number of citati...
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