Locate And Retrieve &Nbsp; Search For Documents Quickly.

　　 Location retrieval Quick search for documents

　　 Enterprise documents In hundreds of thousands of articles, employees can still clearly locate the articles he wants. When the number of articles has accumulated to hundreds of thousands or even more, users will encounter difficulties in retrieving these documents, unable to find what they want, or entering documents after entering the topic words beyond the needs, like looking for a needle in a haystack. To solve this problem, we can start with the following methods:

First, increasing the convenience of retrieval can be achieved through the establishment of a complete set of naming rules. Electronic document The naming is exquisite. For example, a document is called "notice". If you look at the title, you can not know what the notice is about, and the user can not know the core of the document. Therefore, users should create documents in accordance with uniform and standardized naming rules to create documents, enabling users to retrieve them quickly through the title of documents. Such as: company name + department name + content + version number and a series of characters to show the core content of this document.

The factors that need to be considered are how to define the naming of a document. There are three principles: first, consider whether the person who has not read the document can understand the content of the document after reading the title; two, whether the naming rule clearly displays the core content of the document through the subject matter; and three, whether the character contained in the document contains the main meaning of the document. If every employee can name the document according to the naming rules in the knowledge management, everyone can retrieve the location quickly.

Second, by setting keywords, abstracts, directories or some core information in the text, users can retrieve corresponding documents by keywords and abstracts. This is a very exhausting work for many enterprises. In particular, some enterprises have been in operation for ten years or even twenty years. The number of documents accumulated inside the enterprise is very large. It is very difficult to extract the keywords from each document and so on. It is suggested that some key points should be selected for the selection of key documents, such as keywords and abstracts. There is no need to do such work for a large number of common documents.

Third, locate the document through multidimensional classification retrieval. Enterprises can classify documents according to different latitudes through more different latitudes. There are many classification methods when setting multidimensional classification attributes, some of which are applicable to any enterprise. For example, all enterprises contain such documents: company news, enterprise rules and regulations, meeting minutes and so on. You can add labels to these documents by setting the classification properties. For example, we can extract all the documents with "appointed" labels from the system through the label of "appointment". Some dimensions are related to the business characteristics of an enterprise. For example, documents obtained from real estate enterprises from the initial land acquisition to the final sale process can be formulated into multi-dimensional classification attributes. Real estate enterprises can also search the information related documents of all real estate according to the property of the property. In some pharmaceutical enterprises, they can also be classified according to the "disease" dimension according to various diseases, and can also be classified according to the departments of the hospital. Therefore, when setting up a multidimensional classification, enterprises can refer to the classification dimension of the contents of the documents contained in the general enterprise, and also set up the contents of the multidimensional classification attributes according to the business mode and business characteristics of the enterprises.

When you set up multidimensional attribute classification, you will encounter a common problem: if the multidimensional classification property of the document is very large, it will cause some trouble to users. For example, when a user creates or uploads a document, he should choose not only the directory but also the attributes associated with the document. This correlation needs the user's own judgement. If the attributes of the multidimensional classification are set up very much, it is very difficult for the user to decide which attribute is categorized by the document. Therefore, when enterprises set up multi-dimensional classification attributes, we must grasp the balance, and the dimensions should not be too small or too many, which can not only satisfy the needs of enterprises to quickly retrieve documents through multi-dimensional, but also do not cause users any trouble.

In addition, there are other tools and methods to help users quickly retrieve and locate documents. Such as advanced query, advanced search and so on. Another important content is knowledge map management. By setting up multi door knowledge map, users can quickly locate the document. For example, knowledge map can be set up for financial related content, and knowledge map can be set up according to different management fields such as human resources and so on. If the sales personnel must have the quality, job characteristics, job characteristics and other documents are all placed on the knowledge map of the sales staff, it is convenient for users to retrieve the documents related to sales quickly, and quickly retrieve them through knowledge map.