For complex data types such as multimedia, traditional data management methods are not suitable. Instead of attribute matching approaches, access methods based on object similarity are becoming popular. Recently, this resulted in an intensive research of indexing and searching methods for the similarity-based retrieval. Nowadays, many efficient methods are already available, but using them to build an actual search system still requires specialists that tune the methods and build the system manually. Several attempts have already been made to provide a more convenient high-level interface in a form of query languages for such systems, but these are limited to support only basic similarity queries. In this paper, we propose a new language that allows to formulate content-based queries in a flexible way, taking into account the functionality offered by a particular search engine in use. To ensure this, the language is based on a general data model with an abstract set of operations. Consequently, the language supports various advanced query operations such as similarity joins, reverse nearest neighbor queries, or distinct kNN queries, as well as multi-object and multi-modal queries. The language is primarily designed to be used with the MESSIF framework for content-based searching but can be employed by other retrieval systems as well.
The growth of multimedia is increasing the need for standards for accessing and searching distributed repositories. The moving picture experts group (MPEG) is developing the MPEG query format (MPQF) to standardize this interface as part of MPEG-7. The objective is to make multimedia access and search easier and interoperable across search engines and repositories. This article describes the MPQF and highlights some of the ways it goes beyond today's query languages by providing capabilities for multimedia query-by-example and spatiotemporal queries. We present in this paper the MPEG-7 Query Language (MP7QL), a powerful query language that we have developed for querying MPEG-7 descriptions, as well as its compatible Filtering and Search Preferences (FASP) model. The MP7QL has the MPEG-7 as data model and allows for querying every aspect of an MPEG-7 multimedia content description. It allows the users to express the conditions that should hold for the multimedia content returned to them regarding semantics, low-level visual and audio features and media-related aspects. The MP7QL queries may utilize the users' FASP and Usage History as context, thus allowing for personalized multimedia content retrieval. The FASP model supported is compatible with the MP7QL and has the model of the standard MPEG-7 FASPs as a special case. The proposed FASPs essentially are MP7QL queries. Both the MP7QL and its compatible FASP model allow for the exploitation of domain knowledge encoded using pure MPEG-7 constructs. In addition, they allow the explicit specification of boolean operators and or preference values in order to allow both the combination of the query conditions according to the user intentions and the expression of the importance of the individual conditions for the users. The MP7QL query results are represented as MPEG-7 documents, guaranteeing the closure of the results within the MPEG-7 space. The MP7QL and the FASP model have been expressed using both XML Schema and OWL syntax. An implementation of the MP7QL, on top of an XML Native Database is currently in progress. A real world-world evaluation study on the expressive power of the MP7QL shows that it covers both general purpose and domain specific requirements in multimedia content retrieval.