The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Travel route recommendation using geotagged photos
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These various studies point to the underexploited potential for social media data to inform the DMO's strategic decisions [36].”
From A Big Data Analytics Method for Tourist Behaviour Analysis (2017) · cites this paper as [36]
Citations
Cites
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337
A note on two problems in connexion with graphs
Dijkstra, E. (1959) · Numerische Mathematik · doi:10.1007/bf01386390 · Cited by 24,351
Evaluating collaborative filtering recommender systems
Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T. (2004) · ACM Transactions on Information Systems · doi:10.1145/963770.963772 · Cited by 5,798
Photo tourism: exploring photo collections in 3D
Snavely, N., Seitz, S. M., & Szeliski, R. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141964 · Cited by 3,071
A guided tour to approximate string matching
Navarro, G. (2001) · ACM Computing Surveys · doi:10.1145/375360.375365 · Cited by 2,660
Modeling the World from Internet Photo Collections
Snavely, N., Seitz, S. M., & Szeliski, R. (2007) · International Journal of Computer Vision · doi:10.1007/s11263-007-0107-3 · Cited by 2,209
Stoer, J. (1999) · Springer-Lehrbuch · doi:10.1007/978-3-662-09021-3 · Cited by 2,077
Probabilistic Latent Semantic AnalysisPreprint
Hofmann, T. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.6705 · Cited by 2,062
Mining interesting locations and travel sequences from GPS trajectories
Zheng, Y., Zhang, L., Xie, X., & Ma, W. (2009) · International World Wide Web Conference (WWW) · doi:10.1145/1526709.1526816 · Cited by 1,992
Using GPS to learn significant locations and predict movement across multiple users
Ashbrook, D., & Starner, T. E. (2003) · Personal and Ubiquitous Computing · doi:10.1007/s00779-003-0240-0 · Cited by 1,067
Cited by
Big data in tourism research: A literature review
Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018) · Tourism Management · doi:10.1016/j.tourman.2018.03.009 · Cited by 1,200
A Big Data Analytics Method for Tourist Behaviour Analysis
Miah, S. J., Vu, H. Q., Gammack, J., & McGrath, M. (2017) · Information & Management · doi:10.1016/j.im.2016.11.011 · Cited by 393
Palomares, J. C. G., Puebla, J. G., & García, M. D. C. M. (2015) · Applied Geography · doi:10.1016/j.apgeog.2015.08.002 · Cited by 388
Tourists' digital footprint in cities: Comparing Big Data sources
Salas-Olmedo, M. H., Moya‐Gómez, B., Palomares, J. C. G., & Puebla, J. G. (2017) · Tourism Management · doi:10.1016/j.tourman.2017.11.001 · Cited by 282
Lim, K. H., Chan, J., Leckie, C. A., & Karunasekera, S. A. (2017) · Knowledge and Information Systems · doi:10.1007/s10115-017-1056-y · Cited by 197
Metadata
- Authors
- Kurashima, T., Iwata, T., Irie, G., & Fujimura, K.
- Affiliations
- NTT (Japan) (JP)
- Corresponding author
- Kurashima, Takeshi
- Venue
- Knowledge and Information Systems
- Published
- 2012-10-23
- Volume
- 37
- Issue
- 1
- Pages
- 37-60
- ISSN
- 0219-1377 (ISSN-L)
- 0219-3116
- OpenAlex
- W2048272530
- Cited by
- 108
- References
- 33
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 12 · 2022: 13 · 2021: 12 · 2020: 13 · 2019: 13 · 2018: 8 · 2017: 12 · 2016: 10 · 2015: 4 · 2014: 3
- FWCI
- 6.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Knowledge and Information Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Physical Sciences › Computer Science › Information Systems › Data Management and Algorithms
- Keywords
- route recommendation, geotagged photos, location history, topic modeling, Markov model, Flickr
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
