Deriving human activity from geo-located data by ontological and statistical reasoning
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dashdorj, Zolzaya | - |
dc.contributor.author | Sobolevsky, Stanislav | - |
dc.contributor.author | Lee, SangKeun | - |
dc.contributor.author | Ratti, Carlo | - |
dc.date.accessioned | 2021-09-02T13:55:27Z | - |
dc.date.available | 2021-09-02T13:55:27Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2018-03-01 | - |
dc.identifier.issn | 0950-7051 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/76789 | - |
dc.description.abstract | Every day, billions of geo-referenced data (e.g., mobile phone data records, geo-tagged social media, gps records, etc.) are generated by user activities. Such data provides inspiring insights about human activities and behaviors, the discovery of which is important in a variety of domains such as social and economic development, urban planning, and health prevention. The major challenge in those areas is that interpreting such a big stream of data requires a deep understanding of context where each activity occurs. In this study, we use a geographical information data, OpenStreetMap (OSM) to enrich such context with possible knowledge. We build a combined logical and statistical reasoning model for inferring human activities in qualitative terms in a given context. An extensive validation of the model is performed using separate data-sources in two different cities. The experimental study shows that the model is proven to be effective with a certain accuracy for predicting the context of human activity in mobile phone data records. (C) 2017 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.subject | HUMAN MOBILITY | - |
dc.title | Deriving human activity from geo-located data by ontological and statistical reasoning | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, SangKeun | - |
dc.identifier.doi | 10.1016/j.knosys.2017.11.038 | - |
dc.identifier.scopusid | 2-s2.0-85037573451 | - |
dc.identifier.wosid | 000425199600018 | - |
dc.identifier.bibliographicCitation | KNOWLEDGE-BASED SYSTEMS, v.143, pp.225 - 235 | - |
dc.relation.isPartOf | KNOWLEDGE-BASED SYSTEMS | - |
dc.citation.title | KNOWLEDGE-BASED SYSTEMS | - |
dc.citation.volume | 143 | - |
dc.citation.startPage | 225 | - |
dc.citation.endPage | 235 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | HUMAN MOBILITY | - |
dc.subject.keywordAuthor | Ontology | - |
dc.subject.keywordAuthor | Spatial data | - |
dc.subject.keywordAuthor | Human activity recognition | - |
dc.subject.keywordAuthor | Knowledge management | - |
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