scholarly journals Rethinking the usage and experience of clustering markers in web mapping

2019 ◽  
Author(s):  
Loïc Fürhoff
Keyword(s):  
Two Dimensions ◽  
Performance Bottlenecks ◽  
Client Server ◽  
Web Mapping ◽  
Web Map ◽  
Perceived Performance ◽  
Reduction Methods ◽  
Clustering Aggregation ◽  
Clutter Reduction ◽  
Real Challenge

Although the notion of ‘too many markers’ have been mentioned in several research, in practice, displaying hundreds of Points of Interests (POI) on a web map in two dimensions with an acceptable usability remains a real challenge. Web practitioners often make an excessive use of clustering aggregation to overcome performance bottlenecks without successfully resolving issues of perceived performance. This paper tries to bring a broad awareness by identifying sample issues which describe a general reality of clustering, and provide a pragmatic survey of potential technologies optimisations. At the end, we discuss the usage of technologies and the lack of documented client-server workflows, along with the need to enlarge our vision of the various clutter reduction methods.

Clustering aggregation by probability accumulation

2009 ◽  
Vol 42 (5) ◽  
pp. 668-675 ◽  
Author(s):  
Xi Wang ◽  
Chunyu Yang ◽  
Jie Zhou
Keyword(s):  
Probability Accumulation ◽  
Clustering Aggregation

scholarly journals Fabrication of an Organo-Fluoride–Free Hydrophobic Film Using the Sol-Gel Method by Factors Screening and Poly-Acrylic Acid Addition

Coatings ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1011
Author(s):  
Meng-Wei Shen ◽  
Shyi-Tien Chen
Keyword(s):  
Acrylic Acid ◽  
Sol Gel ◽  
Weight Ratio ◽  
Hydrophobic Surface ◽  
Molar Ratio ◽  
Gel Method ◽  
Sol Gel Method ◽  
Static Water ◽  
Clustering Aggregation ◽  
Poly Acrylic Acid

Improving silica film’s contact angle (CA) using tetraethoxysilane (TEOS) and iso-butyltrimethoxysilane (iso-BTMS) by the sol-gel method without adding organo-fluoride substances is of interest. Five factors, namely type of solvent, molar ratio and amounts of TEOS and iso-BTMS, mixing intensity, sol aging time, and presence and absence of poly-acrylic acid (PAA), were assessed to improve the static water CA of the film and its surface quality. Results revealed that when ethanol was used as the dissolving solvent and after adding initial iso-BTMS and TEOS concentrations of 0.0270 and 0.0194 mol/L (molar ratio = 1.39), respectively, without sonication and adding PAA/TEOS weight ratio of 0.029, then the maximum static CA of the film reached 147°, a nearly super-hydrophobic surface. Under given conditions, long-term film durability was observed, and the added PAA prevented the formation of nonhomogeneous film surfaces caused by the highly clustering aggregation of silanols under high pH conditions.

How to Control Clustering Results? Flexible Clustering Aggregation

2009 ◽  
pp. 59-70 ◽  
Author(s):  
Martin Hahmann ◽  
Peter B. Volk ◽  
Frank Rosenthal ◽  
Dirk Habich ◽  
Wolfgang Lehner
Keyword(s):  
Clustering Aggregation

scholarly journals Rethinking the usage and experience of clustering markers in web mapping

2019 ◽  
Author(s):  
Loïc Fürhoff
Keyword(s):  
Two Dimensions ◽  
Performance Bottlenecks ◽  
Client Server ◽  
Web Mapping ◽  
Web Map ◽  
Perceived Performance ◽  
Reduction Methods ◽  
Clustering Aggregation ◽  
Clutter Reduction ◽  
Real Challenge

Although the notion of ‘too many markers’ have been mentioned in several research, in practice, displaying hundreds of Points of Interests (POI) on a web map in two dimensions with an acceptable usability remains a real challenge. Web practitioners often make an excessive use of clustering aggregation to overcome performance bottlenecks without successfully resolving issues of perceived performance. This paper tries to bring a broad awareness by identifying sample issues which describe a general reality of clustering, and provide a pragmatic survey of potential technologies optimisations. At the end, we discuss the usage of technologies and the lack of documented client-server workflows, along with the need to enlarge our vision of the various clutter reduction methods.

Efficient Clustering Aggregation Based on Data Fragments

2012 ◽  
Vol 42 (3) ◽  
pp. 913-926 ◽  
Author(s):  
Ou Wu ◽  
Weiming Hu ◽  
Stephen J. Maybank ◽  
Mingliang Zhu ◽  
Bing Li
Keyword(s):  
Clustering Aggregation
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