[论文收集] HCOMP 2011概况及收录论文

这是第三届HCOMP， 前两届都是傍着KDD， 这次傍了AAAI。

全称：The 3rd Human Computation Workshop (HCOMP 2011)

时间：August 8, 2011 （这次开了一整天）

地点：San Francisco, CA

收录论文情况：一份technical report, 32篇论文（其中16篇是poster）

主页和CFP中一些介绍信息

• 对human computation的介绍："a relatively new research area that studies how to build intelligent systems that involves human computers, with each of them performing computation (e.g., image classification, translation, and protein folding) that leverage human intelligence, but challenges even the most sophisticated AI algorithms that exist today. "
  • 可与上一届中的介绍对比着看： "a relatively new research area that studies the process of channeling the vast internet population to perform tasks or provide data towards solving difficult problems that no known efficient computer algorithms can yet solve."
• 提到的交叉领域：
  • machine learning
  • mechanism and market design
  • information retrieval
  • decision-theoretic planning
  • optimization
  • human computer interaction

CFP中列出的方向：

•Programming languages, tools and platforms to support human computation

•Domain-specific challenges in human computation

•Methods for estimating the cost, reliability, and skill of labelers

•Methods for designing and controlling workflows for human computation tasks

•Empirical and formal models of incentives in human computation systems

•Benefits of one-time versus repeated labeling

•Design of manipulation-resistance mechanisms in human computation

•Concerns regarding the protection of labeler identities

•Active learning from imperfect human labelers

•Techniques for inferring expertise and routing tasks

•Theoretical limitations of human computation

 

Workshop提供的tutorial

以下是收录的论文列表（TOC@aaai）（可下载）

SESSION 1: AI / Machine Learning （4篇）

• Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds

          Sudheendra Vijayanarasimhan, Kristen Grauman (UT Austin)

• Robust Active Learning using Crowdsourced Annotations for Activity Recognition

          Liyue Zhao, Gita Sukthankar (UCF); Rahul Sukthankar (Google Research/CMU)

• Beat the Machine: Challenging workers to find the unknown unknowns

          Josh Attenberg, Panos Ipeirotis, Foster Provost (NYU)

• Human Intelligence Needs Artificial Intelligence

          Daniel Weld, Mausam, Peng Dai (University of Washington)

Poster Session 1 （8篇）

• Towards Task Recommendation in Micro-Task Markets

          Vamsi Ambati, Stephan Vogel, Jaime Carbonell (CMU)

• On Quality Control and Machine Learning in Crowdsourcing

          Matthew Lease (UT Austin)

• CollabMap: Augmenting Maps using the Wisdom of Crowds

          Ruben Stranders, Sarvapali Ramchurn, Bing Shi, Nicholas Jennings (University of Southampton)

• Improving Consensus Accuracy via Z-score and Weighted Voting

          Hyun Joon Jung, Matthew Lease (UT Austin)

• Making Searchable Melodies: Human vs. Machine

          Mark Cartwright, Zafar Rafii, Jinyu Han, Bryan Pardo (Northwestern University)

• PulaCloud: Using Human Computation to Enable Development at the Bottom of the Economic Ladder

          Andrew Schriner (University of Cincinnati); Daniel Oerther (Missouri University of Science and Technology); James Uber (University of Cincinnati)

• Towards Large-Scale Processing of Simple Tasks with Mechanical Turk

          Paul Wais, Shivaram Lingamneni, Duncan Cook, Jason Fennell, Benjamin Goldenberg, Daniel Lubarov, David Marin, Hari Simons (Yelp, inc.)

• Learning to Rank From a Noisy Crowd

          Abhimanu  Kumar, Matthew Lease (UT Austin)

SESSION 2: The “Humans” in the Loop （3篇）

• Worker Motivation in Crowdsourcing and Human Computation

           Nicolas Kaufmann; Thimo Schulze (University of Mannheim)

• Honesty in an Online Labor Market

          Winter Mason, Siddharth Suri, Daniel Goldstein (Yahoo! Research)

• Building a Persistent Workforce on Mechanical Turk for Multilingual Data Collection

          David Chen (UT Austin); William Dolan (Microsoft Research)

SESSION 3: Tools / Applications （2篇）

• CrowdSight: Rapidly Prototyping Intelligent Visual Processing Apps

          Mario Rodriguez (UCSC); James Davis

• Digitalkoot: Making Old Archives Accessible Using Crowdsourcing

          Otto Chrons, Sami Sundell (Microtask)

SESSION 4: Quality Control （4篇）

• Error Detection and Correction in Human Computation: Lessons from the WPA

          David Alan Grier (GWU)

• Programmatic gold: targeted and scalable quality assurance in crowdsourcing

          Dave Oleson, Vaughn Hester, Alex Sorokin, Greg Laughlin, John Le, Lukas Biewald (CrowdFlower)

• An Iterative Dual Pathway Structure for Speech-to-Text Transcription

          Beatrice Liem, Haoqi Zhang, Yiling Chen (Harvard University)

• An Extendable Toolkit for Managing Quality of Human-based Electronic Services

          David Bermbach, Robert Kern, Pascal Wichmann, Sandra Rath, Christian Zirpins (KIT)

Poster Session 2 （8篇）

• Developing Scripts to Teach Social Skills: Can the Crowd Assist the Author?

          Fatima Boujarwah, Jennifer Kim, Gregory Abowd, Rosa Arriaga (Georgia Tech)

• CrowdLang - First Steps Towards Programmable Human Computers for General Computation

          Patrick Minder, Abraham Bernstein (University of Zurich)

• Ranking Images on Semantic Attributes using CollaboRank

          Jeroen Janssens, Eric Postma, Jaap Van den Herik (Tilburg University)

• Artificial Intelligence for Artificial Artificial Intelligence

          Peng Dai, Mausam, Daniel Weld (University of Washington)

• One Step beyond Independent Agreement: A Tournament Selection Approach for Quality Assurance of Human Computation Tasks

          Yu-An Sun, Shourya Roy (Xerox); Greg Little (MIT CSAIL)

• Turkomatic: Automatic, Recursive Task and Workflow Design for Mechanical Turk

          Anand Kulkarni, Matthew Can, Bjoern Hartmann (UC Berkeley)

• MuSweeper: Collect Mutual Exclusions with Extensive Game

          Tao-Hsuan Chang, Cheng-wei Chan, Jane Yung-jen Hsu (National Taiwan University)

• MobileWorks: A Mobile Crowdsourcing Platform for Workers  at the Bottom of the Pyramid

          Prayag Narula, Philipp Gutheim, David Rolnitzky, Anand Kulkarni, Bjoern Hartmann (UC Berkeley)

SESSION 5: Pricing and Allocation （3篇）

• What’s the Right Price? Pricing Tasks for Finishing on Time

          Siamak Faridani, Bjoern Hartmann (UC Berkeley); Panos Ipeirotis (NYU)

• Pricing Mechanisms for Online Labor Market

          Yaron Singer, Manas Mittal (UC Berkeley EECS)

• Labor Allocation in Paid Crowdsourcing: Experimental Evidence on Positioning, Nudges and Prices

          John Horton (ODesk); Dana Chandler (MIT)

转载于:https://www.cnblogs.com/yuquanlaobo/archive/2011/12/23/2295116.html