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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F12%3A00057425%21RIV13-GA0-14330___
rdf:type
n9:Vysledek skos:Concept
dcterms:description
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 exible 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. 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 exible 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.
dcterms:title
Query Language for Complex Similarity Queries Query Language for Complex Similarity Queries
skos:prefLabel
Query Language for Complex Similarity Queries Query Language for Complex Similarity Queries
skos:notation
RIV/00216224:14330/12:00057425!RIV13-GA0-14330___
n9:predkladatel
n18:orjk%3A14330
n3:aktivita
n15:P
n3:aktivity
P(GAP103/10/0886), P(GD102/09/H042)
n3:dodaniDat
n10:2013
n3:domaciTvurceVysledku
n6:3165647 n6:1235753 n6:8876398
n3:druhVysledku
n16:O
n3:duvernostUdaju
n17:S
n3:entitaPredkladatele
n8:predkladatel
n3:idSjednocenehoVysledku
163857
n3:idVysledku
RIV/00216224:14330/12:00057425
n3:jazykVysledku
n4:eng
n3:klicovaSlova
query language; SQL; similarity search
n3:klicoveSlovo
n11:SQL n11:similarity%20search n11:query%20language
n3:kontrolniKodProRIV
[4E2F0565CEAE]
n3:obor
n5:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n12:GAP103%2F10%2F0886 n12:GD102%2F09%2FH042
n3:rokUplatneniVysledku
n10:2012
n3:tvurceVysledku
Batko, Michal Budíková, Petra Zezula, Pavel
n13:organizacniJednotka
14330