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ACM Transactions on Intelligent Systems and Technology (TIST) - Special Issue on Crowd in Intelligent Systems, Research Note/Short Paper and Regular Papers, Volume 7 Issue 4, July 2016

Section: Special Issue: Crowd in Intelligent Systems

Introduction to the Special Issue on Crowd in Intelligent Systems
Kuan-Ta Chen, Omar Alonso, Martha Larson, Irwin King
Article No.: 44
DOI: 10.1145/2920522

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
DOI: 10.1145/2776896

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, BeeWatch, which...

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
DOI: 10.1145/2897365

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
DOI: 10.1145/2897366

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
DOI: 10.1145/2856102

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
DOI: 10.1145/2897367

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
DOI: 10.1145/2897368

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
DOI: 10.1145/2897369

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
DOI: 10.1145/2897370

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
DOI: 10.1145/2873064

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
DOI: 10.1145/2873065

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
DOI: 10.1145/2873063

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
DOI: 10.1145/2870649

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...

Section: Research Note/Short Paper

Modality-Dependent Cross-Media Retrieval
Yunchao Wei, Yao Zhao, Zhenfeng Zhu, Shikui Wei, Yanhui Xiao, Jiashi Feng, Shuicheng Yan
Article No.: 57
DOI: 10.1145/2775109

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...

Section: Regular Papers

Designing Noise-Minimal Rotorcraft Approach Trajectories
Robert Morris, Matthew Johnson, K. Brent Venable, James Lindsey
Article No.: 58
DOI: 10.1145/2838738

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
DOI: 10.1145/2842631

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...

Efficient Generalized Fused Lasso and Its Applications
Bo Xin, Yoshinobu Kawahara, Yizhou Wang, Lingjing Hu, Wen Gao
Article No.: 60
DOI: 10.1145/2847421

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....

Multimodular Text Normalization of Dutch User-Generated Content
Sarah Schulz, Guy De Pauw, Orphée De Clercq, Bart Desmet, Véronique Hoste, Walter Daelemans, Lieve Macken
Article No.: 61
DOI: 10.1145/2850422

As social media constitutes a valuable source for data analysis for a wide range of applications, the need for handling such data arises. However, the nonstandard language used on social media poses problems for natural language processing (NLP)...

Robust Decentralized Low-Rank Matrix Decomposition
István Hegedűs, Árpád Berta, Levente Kocsis, András A. Benczúr, Márk Jelasity
Article No.: 62
DOI: 10.1145/2854157

Low-rank matrix approximation is an important tool in data mining with a wide range of applications, including recommender systems, clustering, and identifying topics in documents. When the matrix to be approximated originates from a large...

Telco User Activity Level Prediction with Massive Mobile Broadband Data
Chen Luo, Jia Zeng, Mingxuan Yuan, Wenyuan Dai, Qiang Yang
Article No.: 63
DOI: 10.1145/2856057

Telecommunication (telco) operators aim to provide users with optimized services and bandwidth in a timely manner. The goal is to increase user experience while retaining profit. To do this, knowing the changing behavior patterns of users through...

Coranking the Future Influence of Multiobjects in Bibliographic Network Through Mutual Reinforcement
Senzhang Wang, Sihong Xie, Xiaoming Zhang, Zhoujun Li, Philip S. Yu, Yueying He
Article No.: 64
DOI: 10.1145/2897371

Scientific literature ranking is essential to help researchers find valuable publications from a large literature collection. Recently, with the prevalence of webpage ranking algorithms such as PageRank and HITS, graph-based algorithms have been...

Multitask Low-Rank Affinity Graph for Image Segmentation and Image Annotation
Teng Li, Bin Cheng, Bingbing Ni, Guangchan Liu, Shuicheng Yan
Article No.: 65
DOI: 10.1145/2856058

This article investigates a low-rank representation--based graph, which can used in graph-based vision tasks including image segmentation and image annotation. It naturally fuses multiple types of image features in a framework named multitask...