Gargiulo, Francesco
(2017)
A Semantic Index for Linked Open Data and Big Data Applications.
[Tesi di dottorato]
| Item Type: |
Tesi di dottorato
|
| Lingua: |
English |
| Title: |
A Semantic Index for Linked Open Data and Big Data Applications |
| Creators: |
| Creators | Email |
|---|
| Gargiulo, Francesco | f.gargiulo@cira.it |
|
| Date: |
10 April 2017 |
| Number of Pages: |
106 |
| Institution: |
Università degli Studi di Napoli Federico II |
| Department: |
Ingegneria Elettrica e delle Tecnologie dell'Informazione |
| Dottorato: |
Ingegneria informatica ed automatica |
| Ciclo di dottorato: |
28 |
| Coordinatore del Corso di dottorato: |
| nome | email |
|---|
| Garofalo, Francesco | francesco.garofalo@unina.it |
|
| Tutor: |
| nome | email |
|---|
| Picariello, Antonio | UNSPECIFIED | | Moscato, Vincenzo | UNSPECIFIED |
|
| Date: |
10 April 2017 |
| Number of Pages: |
106 |
| Uncontrolled Keywords: |
Large databases, distributed index, multiple queries, k-nearest neighbor query algorithm, semantic query |
| Settori scientifico-disciplinari del MIUR: |
Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni |
[error in script]
[error in script]
| Date Deposited: |
09 Jun 2017 08:07 |
| Last Modified: |
14 Mar 2018 13:35 |
| URI: |
http://www.fedoa.unina.it/id/eprint/11524 |
| DOI: |
10.6093/UNINA/FEDOA/11524 |
Abstract
This work proposes a new approach to index multidimensional data based on kd-trees and proposes also a novel approach to query processing. The indexing data structure is distributed across a network of "peers", where each one hosts a part of the tree and uses message passing for communication among nodes. The advantages of this kind of approach are mainly two: it is possible to i) handle a larger number of nodes and points than a single peer based architecture and ii) to run in an efficient way the elaboration of multiple queries. In particular, we propose a novel version of the k-nearest neighbor algorithm that is able to start a query in a randomly chosen peer. Furthrmore, it returns the results without traverse the peer containing the root. Preliminary experiments demonstrated that on average in about 65% of cases a query starting in a random node, does not involve the peer containing the root of the tree. Also, on average in about 98% of cases, it returns the results without involving the root peer. This work also proposes an approach to cope with textual data and provides a way to perform semantic query over the text.
Downloads per month over past year
Actions (login required)
 |
View Item |
