Research and Implementation of Automatic Indexing Method of PDF for Digital Publishing

Abstract

With the rapid development of mobile Internet technology and artificial intelligence technology, the digital publishing industry is in urgent need of using intelligent technology to change the current way of content production and service. Most of the e-book resources owned by publishing enterprises are in PDF format, which is not suitable for reading on mobile devices, and it is not convenient to directly extract key information and construct knowledge graph. With this in mind, this article designs a PDF automatic indexing scheme that can identify all the element information in PDF and output structured data automatically and then extract all the key information in it to generate a keyword library with tag weights. The scheme mainly involves two key technical points: parsing PDF based on text features and grammar rules and extracting keywords based on tag weights. The former visualizes the text block in PDF into a rectangular area, divides the elements by clustering algorithm, and, finally, outputs structured data containing all the information. The latter combines the tags and their weights in the structured data and extracts the keywords in it by the inter-word relation algorithm. The structured data and keywords database produced by this scheme can be used to produce intelligent e-book and build knowledge graph, thus helping publishing enterprises to transform from a content service provider to an intelligent knowledge service provider. This transformation can deeply excavate the core value of the content held by the publishing industry and promote the digitization and intelligentization process of the whole industry.