Scientific and technical literature entity integrated ranking method based on associating network

Abstract

The invention discloses a method for comprehensively sorting scientific literature entities based on a connective network, which comprises the following steps: (1) constructing a literature correlation network according to relationship among the literature entities; (2) setting initial sorting values of nodes in the literature correlation network and expressing the initial sorting values of the nodes as vectors v; (3) constructing a correlation matrix A of the literature correlation network; (4) performing normalization of row vectors and normalization of column vectors to matrixes respectively and setting the obtained matrixes to a matrix B and a matrix C respectively; (5) calculating v' equal to B multiplied by (C plus H) multiplied by vT; (6) calculating v' equal to dv'a minus 1; then adding 1 minus d to each element in v' so as to obtain the vector v new, and expressing each component of the vector v new as the current sorting value; and (7) calculating an absolute value of difference between the current sorting value and the old sorting value of each node, and finding the maximum value thereof; if the maximum value is greater than a threshold value, transferring v equal to v new into 5 for continuous iteration; otherwise, expressing each component of the vector v new as a final sorting value of each node and finishing the operation. The comprehensive sorting method overcomes defects in the prior sorting method, sorts the entities in the literature field according to various relationships existing in the literature world; in addition, the experimental result in the literature indicates that the comprehensive sorting method in the literature is more accurate than the prior sorting method.

Description

technical field [0001] The invention belongs to information retrieval in the field of computer science and scientific measurement in the field of management science, and specifically relates to a method for comprehensively sorting scientific and technological literature entities based on an association network. question. Background technique [0002] With the rapid development of science and technology, academic literature is also increasing at a rapid rate. For example, as of December 2006, CNKI has collected 22,266,795 journal papers since 1979. More than 15,000 articles are added every day. This does not include doctoral and master's theses and other literature. There are 1,457,175 articles included in IEEE Xplore, a foreign literature database. Citeseer has 767,516 articles. DBLP has data for 840,000 documents. How to effectively find high-quality literature from these massive literature sources is very important for researchers. Therefore, the document retrieval ...

AI Technical Summary

Problems solved by technology

Secondly, most of the current literature retrieval systems basically only sort the literature, and rarely involve other entities in the literature field, such as the ranking of authors and publication sources

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