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Introduction to the Special Issue on Crowd in Intelligent Systems
Kuan-Ta Chen, Omar Alonso, Martha Larson, Irwin King
Article No.: 44
Crowdsourcing Without a Crowd: Reliable Online Species Identification Using Bayesian Models to Minimize Crowd Size
Advaith Siddharthan, Christopher Lambin, Anne-Marie Robinson, Nirwan Sharma, Richard Comont, Elaine O'mahony, Chris Mellish, René Van Der Wal
Article No.: 45
We present an incremental Bayesian model that resolves key issues of crowd size and data quality for consensus labeling. We evaluate our method using data collected from a real-world citizen science program, B
A Crowd-Powered System for Fashion Similarity Search
Theodoros Semertzidis, Jasminko Novak, Michalis Lazaridis, Mark Melenhorst, Isabel Micheel, Dimitrios Michalopoulos, Martin Böckle, Michael G. Strintzis, Petros Daras
Article No.: 46
Driven by the needs of customers and industry, online fashion search and analytics are recently gaining much attention. As fashion is mostly expressed by visual content, the analysis of fashion images in online social networks is a rich source of...
Rapid Low-Cost Virtual Human Bootstrapping via the Crowd
Michael Borish, Benjamin Lok
Article No.: 47
Virtual human interactions provide an important avenue for training as emergent opportunities arise. In response to a new training need, we propose a framework to rapidly create experiential learning opportunities in the form of a question--answer...
Incentives for Effort in Crowdsourcing Using the Peer Truth Serum
Goran Radanovic, Boi Faltings, Radu Jurca
Article No.: 48
Crowdsourcing is widely proposed as a method to solve a large variety of judgment tasks, such as classifying website content, peer grading in online courses, or collecting real-world data. As the data reported by workers cannot be verified, there...
PPLib: Toward the Automated Generation of Crowd Computing Programs Using Process Recombination and Auto-Experimentation
Patrick M. De Boer, Abraham Bernstein
Article No.: 49
Crowdsourcing is increasingly being adopted to solve simple tasks such as image labeling and object tagging, as well as more complex tasks, where crowd workers collaborate in processes with interdependent steps. For the whole range of complexity,...
Using the Crowd to Improve Search Result Ranking and the Search Experience
Yubin Kim, Kevyn Collins-Thompson, Jaime Teevan
Article No.: 50
Despite technological advances, algorithmic search systems still have difficulty with complex or subtle information needs. For example, scenarios requiring deep semantic interpretation are a challenge for computers. People, on the other hand, are...
Crowdsourcing Empathetic Intelligence: The Case of the Annotation of EMMA Database for Emotion and Mood Recognition
Christina Katsimerou, Joris Albeda, Alina Huldtgren, Ingrid Heynderickx, Judith A. Redi
Article No.: 51
Unobtrusive recognition of the user's mood is an essential capability for affect-adaptive systems. Mood is a subtle, long-term affective state, often misrecognized even by humans. The challenge to train a machine to recognize it from, for example,...
Using Crowdsourcing for Scientific Analysis of Industrial Tomographic Images
Chen Chen, Paweł W. Woźniak, Andrzej Romanowski, Mohammad Obaid, Tomasz Jaworski, Jacek Kucharski, Krzysztof Grudzień, Shengdong Zhao, Morten Fjeld
Article No.: 52
In this article, we present a novel application domain for human computation, specifically for crowdsourcing, which can help in understanding particle-tracking problems. Through an interdisciplinary inquiry, we built a crowdsourcing system...
CITY FEED: A Pilot System of Citizen-Sourcing for City Issue Management
Linlin You, Gianmario Motta, Kaixu Liu, Tianyi Ma
Article No.: 53
Crowdsourcing implies user collaboration and engagement, which fosters a renewal of city governance processes. In this article, we address a subset of crowdsourcing, named citizen-sourcing, where citizens interact with authorities collaboratively...
Leveraging Human Computations to Improve Schematization of Spatial Relations from Imagery
Huaming Rao, Shih-Wen Huang, Wai-Tat Fu
Article No.: 54
The process of generating schematic maps of salient objects from a set of pictures of an indoor environment is challenging. It has been an active area of research as it is crucial to a wide range of context- and location-aware services, as well as...
A Game-Theory Approach for Effective Crowdsource-Based Relevance Assessment
Yashar Moshfeghi, Alvaro Francisco Huertas Rosero, Joemon M. Jose
Article No.: 55
Despite the ever-increasing popularity of crowdsourcing (CS) in both industry and academia, procedures that ensure quality in its results are still elusive. We hypothesise that a CS design based on game theory can persuade workers to perform their...
Crowdsourcing Human Annotation on Web Page Structure: Infrastructure Design and Behavior-Based Quality Control
Shuguang Han, Peng Dai, Praveen Paritosh, David Huynh
Article No.: 56
Parsing the semantic structure of a web page is a key component of web information extraction. Successful extraction algorithms usually require large-scale training and evaluation datasets, which are difficult to acquire. Recently, crowdsourcing...
In this article, we investigate the cross-media retrieval between images and text, that is, using image to search text (I2T) and using text to search images (T2I). Existing cross-media retrieval methods usually learn one couple of projections, by...
Designing Noise-Minimal Rotorcraft Approach Trajectories
Robert Morris, Matthew Johnson, K. Brent Venable, James Lindsey
Article No.: 58
NASA and the international aviation community are investing in the development of a commercial transportation infrastructure that includes the increased use of rotorcraft, specifically helicopters and civil tilt rotors. However, there is...
STCAPLRS: A Spatial-Temporal Context-Aware Personalized Location Recommendation System
Quan Fang, Changsheng Xu, M. Shamim Hossain, G. Muhammad
Article No.: 59
Newly emerging location-based social media network services (LBSMNS) provide valuable resources to understand users’ behaviors based on their location histories. The location-based behaviors of a user are generally influenced by both user...
Generalized fused lasso (GFL) penalizes variables with l1 norms based both on the variables and their pairwise differences. GFL is useful when applied to data where prior information is expressed using a graph over the variables....