Name
Abstract | ||
|---|---|---|
Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases incuding indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for effciently searching uncertain categorical data over distributed environments. We adress two kinds of query over the distributed uncertain databases, one a distributed probabilistic thresholds query, where all results sastisfying the query with probablities that meet a probablistic threshold requirement are returned, and another a distributed top k-queries, where all results optimizing the transfer of the tuples and the time treatment are returned. |
Year | Venue | Keywords |
|---|---|---|
2015 | PROCEEDINGS OF THE 2015 CONFERENCE OF THE INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY | uncertain database,indexating,distributed environment,top-k query,query optimization,threshold query |
Field | DocType | Volume |
Query optimization,Data mining,Query language,RDF query language,Information retrieval,Query expansion,Computer science,Sargable,Web query classification,Uncertain data,Query by Example | Conference | 89 |
ISSN | Citations | PageRank |
1951-6851 | 0 | 0.34 |
References | Authors | |
13 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adel Benaissa | 1 | 0 | 0.34 |
| Salima Benbernou | 2 | 324 | 32.43 |
| Mourad Ouziri | 3 | 26 | 9.81 |
| Soror Sahri | 4 | 15 | 4.93 |