Boosting house price predictions using geo-spatial network embedding (English)
- New search for: Das, Sarkar Snigdha Sarathi
- Further information on Das, Sarkar Snigdha Sarathi:
- https://orcid.org/http://orcid.org/0000-0003-1052-4142
- New search for: Ali, Mohammed Eunus
- New search for: Li, Yuan-Fang
- New search for: Kang, Yong-Bin
- New search for: Sellis, Timos
- New search for: Das, Sarkar Snigdha Sarathi
- Further information on Das, Sarkar Snigdha Sarathi:
- https://orcid.org/http://orcid.org/0000-0003-1052-4142
- New search for: Ali, Mohammed Eunus
- New search for: Li, Yuan-Fang
- New search for: Kang, Yong-Bin
- New search for: Sellis, Timos
In:
Data Mining and Knowledge Discovery
;
35
, 6
;
2221-2250
;
2021
- Article (Journal) / Electronic Resource
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Title:Boosting house price predictions using geo-spatial network embedding
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Additional title:Data Min Knowl Disc
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Contributors:Das, Sarkar Snigdha Sarathi ( author ) / Ali, Mohammed Eunus ( author ) / Li, Yuan-Fang ( author ) / Kang, Yong-Bin ( author ) / Sellis, Timos ( author )
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Published in:Data Mining and Knowledge Discovery ; 35, 6 ; 2221-2250
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Publisher:
- New search for: Springer US
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Place of publication:New York
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Publication date:2021-11-01
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Size:30 pages
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ISSN:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents – Volume 35, Issue 6
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 2221
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Boosting house price predictions using geo-spatial network embeddingDas, Sarkar Snigdha Sarathi / Ali, Mohammed Eunus / Li, Yuan-Fang / Kang, Yong-Bin / Sellis, Timos et al. | 2021
- 2251
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Social media as author-audience gamesRibeiro, Andre F. et al. | 2021
- 2282
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Isolation kernel: the X factor in efficient and effective large scale online kernel learningTing, Kai Ming / Wells, Jonathan R. / Washio, Takashi et al. | 2021
- 2313
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Implicit consensus clustering from multiple graphsBoutalbi, Rafika / Labiod, Lazhar / Nadif, Mohamed et al. | 2021
- 2341
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A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clusteringRandel, Rodrigo / Aloise, Daniel / Blanchard, Simon J. / Hertz, Alain et al. | 2021
- 2369
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Time series clustering in linear time complexityLi, Xiaosheng / Lin, Jessica / Zhao, Liang et al. | 2021
- 2389
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Chebyshev approaches for imbalanced data streams regression modelsAminian, Ehsan / Ribeiro, Rita P. / Gama, João et al. | 2021
- 2467
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Continuous treatment effect estimation via generative adversarial de-confoundingKuang, Kun / Li, Yunzhe / Li, Bo / Cui, Peng / Yang, Hongxia / Tao, Jianrong / Wu, Fei et al. | 2021
- 2498
-
Characterizing attitudinal network graphs through frustration cloudRusnak, Lucas / Tešić, Jelena et al. | 2021
- 2540
-
Introduction to the special issue of the ECML PKDD 2021 journal trackAppice, Annalisa / Escalera, Sergio / Gámez, Jose A. / Trautmann, Heike et al. | 2021
- 2542
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BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descentHess, Sibylle / Pio, Gianvito / Hochstenbach, Michiel / Ceci, Michelangelo et al. | 2021
- 2577
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Early abandoning and pruning for elastic distances including dynamic time warpingHerrmann, Matthieu / Webb, Geoffrey I. et al. | 2021
- 2602
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MultiETSC: automated machine learning for early time series classificationOttervanger, Gilles / Baratchi, Mitra / Hoos, Holger H. et al. | 2021
- 2655
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CURIE: a cellular automaton for concept drift detectionLobo, Jesus L. / Del Ser, Javier / Osaba, Eneko / Bifet, Albert / Herrera, Francisco et al. | 2021
- 2679
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VFC-SMOTE: very fast continuous synthetic minority oversampling for evolving data streamsBernardo, Alessio / Della Valle, Emanuele et al. | 2021
- 2714
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Unsupervised domain adaptation with non-stochastic missing dataKirchmeyer, Matthieu / Gallinari, Patrick / Rakotomamonjy, Alain / Mantrach, Amin et al. | 2021