Query Language for Complex Similarity Queries

Abstract

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.

A new indexing method for complex similarity queries in immersive multimedia systems

“…The query language of [9] allows to formulate content-based queries that support various advanced query operations such as similarity joins, nearest neighbor queries, and multi-object multi-modal queries.…”

The similarity-aware relational division database operator

“…Many researchers have been proposing strategies to support similarity comparison in Relational Database Management Systems -RDBMS [Silva et al 2015, Pola et al 2015, Budíková et al 2012, Belohlavek and Vychodil 2010, commonly by extending Relational Operators. The vast majority of them focuses on the Selection [Silva et al 2013] in which similarity awareness is achieved by means of range queries, nearest neighbors queries, and their many variants.…”

Similarity sets: A new concept of sets to seamlessly handle similarity in database management systems

“…Along with equivalence rules for similarity operators, query execution plans for similarity joins are designed to interact with similarity grouping and similarity join operators, aimed at enabling faster query executions. The work of Budikova et al [7] proposes a query language that allows to formulate content-based queries supporting complex operations, such as similarity joins.…”