Method and device for full-text retrieval document database

Abstract

The invention discloses a method and device for full-text retrieval of a document database, comprising: querying attachments in documents and performing document conversion on the attachments obtained from the query according to a preset policy; library; establish a full-text index catalog for the generated document data sub-library, and store it in a preset relational database; receive the search keywords input by the user, match the full-text index catalog in the relational database, and obtain the matching full-text index catalog corresponding A document in a document database. By applying the invention, the query efficiency of the full-text search can be improved.

Description

technical field [0001] The invention relates to retrieval technology, in particular to a method and device for full-text retrieval of document databases. Background technique [0002] The current development direction of operators in the field of informatization support is to focus on enterprise users and strengthen the collaboration of organizations, processes, and personnel. Among them, the office automation system (OA, Office Automation) and the knowledge management system are indispensable core systems for enterprise informatization. The knowledge documents and official documents involved are generally managed by a document database and a search engine is provided. Users can input key Words are searched to obtain the required document information. [0003] Document databases belong to the category of databases, can share the same data, have physical independence and logical independence of data, separate data and programs, allow the creation of many different types of u...

AI Technical Summary

Problems solved by technology

In the prior art, the documents in the document database are usually queried through the full-text search provided by the document database itself. In this way, when the number of documents is large, the full-text search will often obtain a large result set, and the user is still faced with a massive The data results cannot meet the user's query requirements

Specifically, first of all, the efficiency of full-text search is low. For example, in the application of workflow automation, as the number of official documents increases, the capacity of the document database increases day by day. Due to the increase in database capacity, the ability of the document database to process data is greatly reduced. Especially in terms of data query and retrieval, the time required for query retrieval is greatly increased, and the query efficiency is significantly reduced

Secondly, the query results are inaccurate. Because the search engine embedded in the document database has poor support for full-text retrieval, for example, documents may contain attachments in different formats. For example, a document may contain WORD attachments, PDF attachments, etc., so , when performing full-text retrieval, the document database is required to provide parsers for attachments in different formats in order to retrieve and read the content in the attachments, but the search engine embedded in the document database does not have a parser, so there are differences in documents format, it may cause users to be unable to find the desired document or return a completely irrelevant collection of documents

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