This figure correspond to Steps 6 through 8. This figure corresponds to Ste ps 1 through 5.įigure 7-2 illustrates how the crawler caches Web pages. It also shows how the crawler queues hypertext links to control its navigation. The example uses a Web data source, although the crawler can also crawl other data source types.įigure 7-1 illustrates how the crawler and its crawling threads are activated. If attribute LOV is available, then the crawler registers the LOV definition, which includes attribute value, attribute value display name, and its translation.įigure 7-1 and Figure 7-2 illustrate an instance of the crawling cycle in a sequence of nine steps. The list of v alues (LOV) for a search attribute can help you specify a search query. If not found, then the crawler creates a new search attribute with the same name and type as the document attribute defined in the crawler agent.) (During crawling, the crawler agent maps the document attribute to a search attribute with the same name and data type. Search attributes created by the crawler. Search attributes created by the system administrator System-defined search attributes, such as title, author, description, subject, and mimetype Search attributes can also be created in the following ways: They can be incorporated in search applications for a more detailed search and richer presentation. Oracle Ultra Search has the following default search attributes: Title, Author, Description, Subject, Mimetype, Language, Host, and LastModifedDate. It can also have the same attribute name for different ideas for example, "language" as in natural language in one data source but as programming language in another. Different data sources can have different attribute names which are used for the same idea for example, "version" and "revision".
Document attributes can be used for many things, including document management, access control, or version control. If the document is a Web page, the attribute can come from the HTTP header or it can be embedded inside the HTML in metatags.
Therefore, you can query documents from multiple data sources based on the same search attribute.
Document attributes in different data sources can be mapped to the same search attribute. This lets you query documents based on their attributes. The value is retrieved during the crawling process, then mapped to one of the search attributes, and then stored and indexed in the database. Each data source has its own set of document attributes. Docume nt attributes, or metadata, describe the properties of a document.
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