Basic Approaches for Data Retrieval

Data management has a long history and many approaches have been invented to manage and query diverse data types in the computer systems.As given in [15], the basic approaches being used for data management can be classified into the following categories:

• Conventional database system : This is the widely-used approach to manage and search for structured data. All data in a database system must conform to some predefined structures and constraints (i.e., schema's). To formulate a database query the user must specify which data objects are to be retrieved, the database tables from which they are to be extracted and predicate on which the retrieval is based. A query language for the database will generally be of the artificial kind, one with restricted syntax and vocabulary, such as SQL.
• Information retrieval (IR) system : IR system is mainly used to search large text collections, in which the content of the (text) data is described by an indexer using keywords or a textual abstract, and keywords or natural language is used to express query demands. For example for an image or video we have to describe it in words or in a way need to store lot of metadata (textual form).
• Content based retrieval (CBR) system : This approach is used to retrieve desired multimedia objects from a large collection on the basis of features (such as color, texture and shape, etc.) that can be automatically extracted from the objects themselves. Although keyword can be treated as a ''feature'' for text data, traditional information retrieval has much more higher performance than content-based retrieval because keyword has the proven ability to represent semantics, while no features have shown convincing semantic describing ability. But major drawback of this method is that it lacks precision.
• Graph or tree pattern matching : This approach aims to retrieve object sub-graphs from an object graph according to some denoted patterns.