Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing
In this paper, an innovative geographical locations' rating scheme is presented, which is based on crowdsensing and crowdsourcing. People sense their surrounding space and submit evaluations through: (a) a smartphone application, and (b) a prototype website. Both have been implemented using the...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8755832/ |
| _version_ | 1818412593472077824 |
|---|---|
| author | Klimis S. Ntalianis Andreas Kener Jahna Otterbacher |
| author_facet | Klimis S. Ntalianis Andreas Kener Jahna Otterbacher |
| author_sort | Klimis S. Ntalianis |
| collection | DOAJ |
| description | In this paper, an innovative geographical locations' rating scheme is presented, which is based on crowdsensing and crowdsourcing. People sense their surrounding space and submit evaluations through: (a) a smartphone application, and (b) a prototype website. Both have been implemented using the state-of-the-art technologies. Evaluations are pairs of feeling/state and strength, where six different feelings/states and five strength levels are considered. In addition, the detection of similar locations is proposed by maximizing a cross-correlation criterion through a genetic algorithm approach. Technical details of the overall system are provided so that the interested readers can replicate its components. The experimental results on real-world data, which also include comparisons with Google Maps Rating and Tripadvisor, illustrate the merits and limitations of each technology. Finally, the paper is concluded by uncovering and discussing interesting issues for future research. |
| first_indexed | 2024-12-14T10:49:47Z |
| format | Article |
| id | doaj.art-bcb940be9c5f495fae13b7772be457a4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T10:49:47Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-bcb940be9c5f495fae13b7772be457a42022-12-21T23:05:16ZengIEEEIEEE Access2169-35362019-01-017902159022910.1109/ACCESS.2019.29268128755832Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and CrowdsourcingKlimis S. Ntalianis0https://orcid.org/0000-0002-2175-3306Andreas Kener1Jahna Otterbacher2Department of Business Administration, University of West Attica, Athens, GreeceDepartment of Business Administration, University of West Attica, Athens, GreeceFaculty of Pure and Applied Sciences, Open University of Cyprus, Nicosia, CyprusIn this paper, an innovative geographical locations' rating scheme is presented, which is based on crowdsensing and crowdsourcing. People sense their surrounding space and submit evaluations through: (a) a smartphone application, and (b) a prototype website. Both have been implemented using the state-of-the-art technologies. Evaluations are pairs of feeling/state and strength, where six different feelings/states and five strength levels are considered. In addition, the detection of similar locations is proposed by maximizing a cross-correlation criterion through a genetic algorithm approach. Technical details of the overall system are provided so that the interested readers can replicate its components. The experimental results on real-world data, which also include comparisons with Google Maps Rating and Tripadvisor, illustrate the merits and limitations of each technology. Finally, the paper is concluded by uncovering and discussing interesting issues for future research.https://ieeexplore.ieee.org/document/8755832/Geographical locationvolunteered geographic information (VGI)rating schemecrowdsensingcrowdsourcingfeelings’/states’ evaluation |
| spellingShingle | Klimis S. Ntalianis Andreas Kener Jahna Otterbacher Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing IEEE Access Geographical location volunteered geographic information (VGI) rating scheme crowdsensing crowdsourcing feelings’/states’ evaluation |
| title | Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing |
| title_full | Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing |
| title_fullStr | Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing |
| title_full_unstemmed | Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing |
| title_short | Feelings’ Rating and Detection of Similar Locations, Based on Volunteered Crowdsensing and Crowdsourcing |
| title_sort | feelings x2019 rating and detection of similar locations based on volunteered crowdsensing and crowdsourcing |
| topic | Geographical location volunteered geographic information (VGI) rating scheme crowdsensing crowdsourcing feelings’/states’ evaluation |
| url | https://ieeexplore.ieee.org/document/8755832/ |
| work_keys_str_mv | AT klimissntalianis feelingsx2019ratinganddetectionofsimilarlocationsbasedonvolunteeredcrowdsensingandcrowdsourcing AT andreaskener feelingsx2019ratinganddetectionofsimilarlocationsbasedonvolunteeredcrowdsensingandcrowdsourcing AT jahnaotterbacher feelingsx2019ratinganddetectionofsimilarlocationsbasedonvolunteeredcrowdsensingandcrowdsourcing |