Combination of TA- and MD-algorithm for Efficient Solving of Top-K Problem according to User's Preferences

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F09%3A00207444" target="_blank" >RIV/00216208:11320/09:00207444 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Combination of TA- and MD-algorithm for Efficient Solving of Top-K Problem according to User's Preferences

Popis výsledku v původním jazyce

In this article we focus on efficient solving of searching the best K objects in more attributes according to user?s preferences. Local preferences are modelled with one of four types of fuzzy function. Global preferences are modelled concurrently with an aggregation function. We focused on searching the best K objects according to various user?s preferences without accessing all objects. Therefore we deal with the use of TA-algorithm and MD-algorithm. Because of local preferences we used B+-trees during computing of Fagin?s TA-algorithm. For searching the best K objects MD-algorithm uses multidimensional B-tree, which is also composed of B+-trees. We developed an MXT-algorithm and a new data structure, in which MXT-algorithm can effectively find the best K objects by user?s preferences without accessing all the objects. We show that MXT-algorithm in some cases achieves better results in the number of accessed objects than TA-algorithm and MD-algorithm.

Název v anglickém jazyce

Combination of TA- and MD-algorithm for Efficient Solving of Top-K Problem according to User's Preferences

Popis výsledku anglicky

In this article we focus on efficient solving of searching the best K objects in more attributes according to user?s preferences. Local preferences are modelled with one of four types of fuzzy function. Global preferences are modelled concurrently with an aggregation function. We focused on searching the best K objects according to various user?s preferences without accessing all objects. Therefore we deal with the use of TA-algorithm and MD-algorithm. Because of local preferences we used B+-trees during computing of Fagin?s TA-algorithm. For searching the best K objects MD-algorithm uses multidimensional B-tree, which is also composed of B+-trees. We developed an MXT-algorithm and a new data structure, in which MXT-algorithm can effectively find the best K objects by user?s preferences without accessing all the objects. We show that MXT-algorithm in some cases achieves better results in the number of accessed objects than TA-algorithm and MD-algorithm.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

DATESO 2009

ISBN

978-80-01-04323-3

ISSN

—

e-ISSN

—

Počet stran výsledku

12

Strana od-do

—

Název nakladatele

Czech Technical University in Prague

Místo vydání

—

Místo konání akce

Neuveden

Datum konání akce

1. 1. 2009

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000272412300013