Information searching method based on metadata

Abstract

The invention relates to an information search method based on a metadata, which comprises the following steps during search: step 1, splitting searched words and sentences into key words; the splitting method is scanning the searched words and sentences from front to back, finding and then cutting the longest match in the word stock, continuing to find the longest match in the rest until splitting is finished; step 2, carrying out metadata match analysis on single key word according to the mapping relationship of er model of the metadata; extracting metadata explanation information based on match result and generating match information record of the key words; step 3, integrating the match information record of all the key words and outputting and presenting the results after optimization treatment. By adopting the information search method, the invention can acquire associated information from a plurality of data sources conveniently and overcome the search bottleneck of data warehousing. The invention supports Chinese search with simple operation, which is especially suitable for application in development and management and can improve the development efficiency of developers.

Description

technical field [0001] The invention belongs to the application field of information management, and particularly relates to an information retrieval method based on metadata. Background technique [0002] Relevant surveys show that the current corporate data is growing at a rate of 200% every year. Structured and unstructured data are stored in every corner of the corporate computer system; corporate employees spend an average of two and a half hours a day looking for information. In this way, there are various obstacles in the enterprise, and the information utilization efficiency is extremely low: 1. There is too much data, and it takes a lot of time to obtain useful information. 2. The data is distributed in different application systems, and when the information is needed, it is forgotten where it is stored. Need to convert multiple times to find. 3. Deal with new business and new problems, and do not know what information is available within the organization. 4. The...

AI Technical Summary

Problems solved by technology

In this way, there are various obstacles in the enterprise, and the efficiency of information utilization is extremely low: 1. There is too much data, and it takes a lot of time to obtain useful information

2. The data is distributed in different application systems, and when information is needed, it is forgotten where it is stored

Need to convert multiple times to find

3. To deal with new business and new problems, do not know what information can be used within the organization

4. Adopting a new information management system will often change the working habits of employees, and it will take time and effort to adapt and learn

5. The implementation time and cost of the system itself are relatively high

At present, in order to manage a large amount of data within the enterprise, a data warehouse technology has emerged, but it is not easy to find information from the massive data stored in the data warehouse, because it is difficult to be used by business personnel due to the lack of semantic search technology.

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