Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/1230
DC FieldValueLanguage
dc.contributor.authorVujičić Stanković, Stašaen_US
dc.contributor.authorRakočević, Goranen_US
dc.contributor.authorMilutinović, Veljkoen_US
dc.date.accessioned2022-09-29T16:10:28Z-
dc.date.available2022-09-29T16:10:28Z-
dc.date.issued2011-12-01-
dc.identifier.isbn9781457720161-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/1230-
dc.description.abstractThis paper introduces a new approach to the problem of data mining in wireless sensor networks. The problem is fast emerging, due to recent technological advances in both data mining and wireless sensor networks. The basic, axiomatic, assumption for this research is that a typical decision making process converges faster if some positive knowledge is incorporated into the process, i.e., the knowledge that decreases the probability of wrong decision. The above implies that any data mining process can be improved, if metadata with positive knowledge are added to it. Consequently, the same applies if data mining is performed on top of some wireless sensor network infrastructure. The proposed algorithm is compared with the best one from the open literature, with the final goal to compare the two algorithms analytically and by simulation. It is expected that the proposed algorithm behaves better in all conditions, and much better in conditions of the suddenly changing environment. © 2011 IEEE.en_US
dc.subjectData Miningen_US
dc.subjectWireless Sensor Networksen_US
dc.titleA metadata-supported distributed approach for data mining based prediction in wireless sensor networksen_US
dc.typeConference Paperen_US
dc.relation.publication10th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2011 - Proceedingsen_US
dc.identifier.doi10.1109/TELSKS.2011.6112030-
dc.identifier.scopus2-s2.0-84855845649-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84855845649-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.firstpage181en_US
dc.relation.lastpage185en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeConference Paper-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0002-7200-3724-
Appears in Collections:Research outputs
Show simple item record

SCOPUSTM   
Citations

1
checked on Dec 24, 2024

Page view(s)

7
checked on Dec 24, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.