Matches in SemOpenAlex for { <https://semopenalex.org/work/W2759984148> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W2759984148 endingPage "78" @default.
- W2759984148 startingPage "69" @default.
- W2759984148 abstract "Activity recognition is one of the emerging trends in the domain of mining ubiquitous environments. It assumes that we can recognize the current action undertaken by the monitored subject on the basis of outputs of a set of associated sensors. Often different combinations of smart devices are being used, thus creating an Internet of Things. Such data will arrive continuously during the operation time of sensors and require an online processing in order to keep a real-time track of the current activity being undertaken. This forms a natural data stream problem with the potential presence of changes in the arriving data. Therefore, we require an efficient online machine learning system that can offer high recognition rates and adapt to drifts and shifts in the stream. In this paper we propose an efficient and lightweight adaptive ensemble learning system for real-time activity recognition. We use a weighted modification of Naïve Bayes classifier that can swiftly adapt itself to the current state of the stream without a need for an external concept drift detector. To tackle the multi-class nature of activity recognition problem we propose to use an one-vs-one decomposition to form a committee of simpler and diverse learners. We introduce a novel weighted combination for one-vs-one decomposition that can adapt itself over time. Additionally, to limit the cost of supervision we propose to enhance our classification system with active learning paradigm to select only the most important objects for labeling and work under constrained budget. Experiments carried out on six data streams gathered from ubiquitous environments show that the proposed active and adaptive ensemble offer excellent classification accuracy with low requirement for access to true class labels." @default.
- W2759984148 created "2017-10-06" @default.
- W2759984148 creator A5054879396 @default.
- W2759984148 date "2017-12-01" @default.
- W2759984148 modified "2023-10-17" @default.
- W2759984148 title "Active and adaptive ensemble learning for online activity recognition from data streams" @default.
- W2759984148 cites W1747692387 @default.
- W2759984148 cites W1945209586 @default.
- W2759984148 cites W1963743786 @default.
- W2759984148 cites W1970693311 @default.
- W2759984148 cites W1971361852 @default.
- W2759984148 cites W1972226726 @default.
- W2759984148 cites W1973991804 @default.
- W2759984148 cites W1981328081 @default.
- W2759984148 cites W1982039810 @default.
- W2759984148 cites W1985157189 @default.
- W2759984148 cites W1989496527 @default.
- W2759984148 cites W2011924202 @default.
- W2759984148 cites W2012528039 @default.
- W2759984148 cites W2038705219 @default.
- W2759984148 cites W2050477740 @default.
- W2759984148 cites W2054780155 @default.
- W2759984148 cites W2058963220 @default.
- W2759984148 cites W2059094808 @default.
- W2759984148 cites W2073256825 @default.
- W2759984148 cites W2093323495 @default.
- W2759984148 cites W2096731057 @default.
- W2759984148 cites W2099419573 @default.
- W2759984148 cites W2139327121 @default.
- W2759984148 cites W2142692934 @default.
- W2759984148 cites W2148972769 @default.
- W2759984148 cites W2150932143 @default.
- W2759984148 cites W2165466912 @default.
- W2759984148 cites W2171253128 @default.
- W2759984148 cites W2193120940 @default.
- W2759984148 cites W2585528949 @default.
- W2759984148 cites W2588336250 @default.
- W2759984148 cites W2705774613 @default.
- W2759984148 cites W2718193527 @default.
- W2759984148 cites W4233583441 @default.
- W2759984148 cites W1919374107 @default.
- W2759984148 doi "https://doi.org/10.1016/j.knosys.2017.09.032" @default.
- W2759984148 hasPublicationYear "2017" @default.
- W2759984148 type Work @default.
- W2759984148 sameAs 2759984148 @default.
- W2759984148 citedByCount "47" @default.
- W2759984148 countsByYear W27599841482018 @default.
- W2759984148 countsByYear W27599841482019 @default.
- W2759984148 countsByYear W27599841482020 @default.
- W2759984148 countsByYear W27599841482021 @default.
- W2759984148 countsByYear W27599841482022 @default.
- W2759984148 countsByYear W27599841482023 @default.
- W2759984148 crossrefType "journal-article" @default.
- W2759984148 hasAuthorship W2759984148A5054879396 @default.
- W2759984148 hasConcept C119857082 @default.
- W2759984148 hasConcept C121687571 @default.
- W2759984148 hasConcept C12267149 @default.
- W2759984148 hasConcept C124101348 @default.
- W2759984148 hasConcept C154945302 @default.
- W2759984148 hasConcept C2778484313 @default.
- W2759984148 hasConcept C41008148 @default.
- W2759984148 hasConcept C52001869 @default.
- W2759984148 hasConcept C60777511 @default.
- W2759984148 hasConcept C76155785 @default.
- W2759984148 hasConcept C89198739 @default.
- W2759984148 hasConcept C95623464 @default.
- W2759984148 hasConceptScore W2759984148C119857082 @default.
- W2759984148 hasConceptScore W2759984148C121687571 @default.
- W2759984148 hasConceptScore W2759984148C12267149 @default.
- W2759984148 hasConceptScore W2759984148C124101348 @default.
- W2759984148 hasConceptScore W2759984148C154945302 @default.
- W2759984148 hasConceptScore W2759984148C2778484313 @default.
- W2759984148 hasConceptScore W2759984148C41008148 @default.
- W2759984148 hasConceptScore W2759984148C52001869 @default.
- W2759984148 hasConceptScore W2759984148C60777511 @default.
- W2759984148 hasConceptScore W2759984148C76155785 @default.
- W2759984148 hasConceptScore W2759984148C89198739 @default.
- W2759984148 hasConceptScore W2759984148C95623464 @default.
- W2759984148 hasLocation W27599841481 @default.
- W2759984148 hasOpenAccess W2759984148 @default.
- W2759984148 hasPrimaryLocation W27599841481 @default.
- W2759984148 hasRelatedWork W1521014365 @default.
- W2759984148 hasRelatedWork W2161835057 @default.
- W2759984148 hasRelatedWork W2329342202 @default.
- W2759984148 hasRelatedWork W2574092225 @default.
- W2759984148 hasRelatedWork W2736127210 @default.
- W2759984148 hasRelatedWork W2740428142 @default.
- W2759984148 hasRelatedWork W2802243998 @default.
- W2759984148 hasRelatedWork W3208495060 @default.
- W2759984148 hasRelatedWork W4200217704 @default.
- W2759984148 hasRelatedWork W4307392573 @default.
- W2759984148 hasVolume "138" @default.
- W2759984148 isParatext "false" @default.
- W2759984148 isRetracted "false" @default.
- W2759984148 magId "2759984148" @default.
- W2759984148 workType "article" @default.