The era of big data means that the amount of data and the structured data and unstructured data are equally important. Enterprise document management mode based on knowledge management attaches importance to knowledge management, knowledge sharing and knowledge innovation. The arrival of big data has put forward new requirements for the mode of knowledge management. The collection mode of existing management mode is narrow. Under the background of big data, the collection of document organizations should be diversified, collecting documents from a wide angle, and paying more attention to the collection of complex, fragmented, and low-level information.

At present, we manage documents from two aspects: document flow and data flow. We pay attention to the front-end control of documents, but we only make simple identification and processing of documents before the documents are generated. Such a process does not reduce the workload of document organizations, but increases the duplication and processing of documents. Redundancy and complexity of document data lead to heavy workload of knowledge extraction and unreliable extraction of knowledge. Therefore, for document front-end control, the method of document identification before document generation and the standardized format of documents are very necessary. Choosing the correct document identification method can quickly distinguish the value of documents and improve the speed of document input, and the standardization of document format is the foundation of digging knowledge.

Talent resource is the key to enterprise document management. The traditional document management mode only requires the staff to have basic knowledge such as filing, collecting data, searching and so on. With the development of electronization and networking, enterprises require the staff of document organization not only to have basic service literacy, but also to understand information technology. However, under the background of big data, enterprise literacy management is far from enough. The document staff should not only understand the modern enterprise management theory, be familiar with the business process, but also have the ability of data processing, and be able to use advanced technology to improve the work ability and efficiency. The staff should look at documents from the perspective of data and promote the management and service of documents with the concept of big data. From the management point of view, we must strictly guard the selection of talents, speed up the transformation of knowledge structure of document personnel, and cultivate talents in multiple ways and at different levels.

　　 technology It is the productivity of enterprise development. In the enterprise document management mode based on knowledge management, technology is the cornerstone of the whole pattern structure. On the whole, the layout of IT architecture is the foundation of the whole knowledge management platform. From a partial point of view, data mining technology is the core technology of knowledge extraction, and is the whole core of knowledge extraction. Enterprise documents The center of management. The core of the whole document management is data mining technology, and all activities are carried out around it. The existing document management mode provides peer to peer personalized services. Under the background of big data, users need more information and knowledge in order to make good decisions in the increasingly competitive environment. This poses new challenges to the services provided by the document bodies of state-owned enterprises. Users require the document organization's service to respond faster, information retrieval and query more convenient, information and knowledge more understandable, and can provide the whole process of information services. This requires the personalized services provided by document organizations under the background of big data not only to provide users with the information they need, but also to pass the right way. user demand To analyze and provide refined knowledge organization output based on mass and distributed resources, that is to realize one-stop service of "information + solution".