Paper Info
Title
histoGraph as a Demonstrator for Domain Specific Challenges to Crowd-Sourcing.
Abstract
histoGraph provides an integrated pipeline for the extraction of cooccurrence information in historical photos to build an exploreable social graph of relationships that can lead to new insights for historical research. The application leverages on the CUbRIK platform for human/machine computation and applies a hybrid approach to face-detection and -recognition that combines the strengths of algorithmic analysis with expert and generic crowd sourcing. Following a general overview of our approach, we explore the surplus value of human touch for the identification of identities in historical image collections through a uniform crowd-sourcing approach. We find that only a combination of generic and expert crowds yields promising results. Even though the application was designed and developed for a specific target audience, we aim not only at demonstrating the current functionality but also identify and discuss several core principles that can be transferred to other domains.
Year
DOI
Venue
2014
10.1007/978-3-319-15168-7_57
Lecture Notes in Computer Science
Keywords
Field
DocType
Face identification,Crowdsourcing,Photographs,Digital humanities,European integration
Data science,Crowds,Data mining,Social graph,Crowdsourcing,Computer science,Surplus value,Target audience,Comparative historical research,Computation
Conference
Volume
ISSN
Citations 
8852
0302-9743
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
Lars Wieneke111.42
Marten Düring245.86
Vincenzo Croce3243.97
Jasminko Novak414822.99