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grate DB access into the code, e.g. to create a record
you only have to declare the object type as persistent
and create a new instance, the rest will be done by the
OODBMS. As methods are related to the objects these
may be stored in the database, too. So the strict separation
between data and functions as proposed by
RDBMS is blurred. Because OODBMS allow other
than elementary data types, SQL cannot be the query
language. Therefore the Object Query Language
(OQL) has been standardized by the Object Database
Management Group (ODMG).
3.1.3 Text Oriented DBMS
Text oriented database management systems or information
retrieval systems were designed to get meaningful
results when searching in huge amounts of
documents, e.g. literature search. They often allow for
natural language querying. To get meaningful results
documents are indexed when stored in the database.
For relevant words so called „inverted lists“ are maintained
which tell which documents contain them and
how important they are, e.g. „computer“ in technical
context provides hardly any information, however in medical context it is really significant.
When querying, these lists are used to calculate a score for documents. Documents with the
highest scores will be shown as hits. A very common techniques which leads to good results is
relevance feedback where the user copies passages from a good result and uses this as starting
point for the next query.
3.2 Image Description
As mentioned above, content based retrieval (CBR) to date can only be done for very simple
applications. This implies, that additional description is necessary for the images. They could
be described using plain text or in a more structured way using key systems or even conceptual
graphs.
3.2.1 Key Systems
Key systems are widely used to define keywords for retrieval. They limit the vocabulary and
thus enable a more unified description. With key systems it is easy to deal with synonyms and
multiple languages. Key systems can be chosen hierarchically, that means that each node has
exactly one parent node (except the root). With this construction different kinds of queries can
be asked. This can be demonstrated with an anatomy example. A search for images with localization
‘finger’ could lead to different results epending d on the mode:
‘=’: All images with exactly the localization ‘finger’ will be etrieved r
‘⊆’: All images with ‘finger’ or parts of the ‘finger’ will be etrieved r
‘⊇’: All images in which a ‘finger’ is visible will retrieved be
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Head
....
....
Whole body view
Foot
Plantae Toe
....
⊆
⊇
....
=
....
Toe-nail
....
Hand
Figure 1: Search using a hierarchical
key
....