@article{vonahn2013augmented, author = {von Ahn, Luis}, doi = {10.1098/rsta.2012.0383}, eprint = {http://rsta.royalsocietypublishing.org/content/371/1987/20120383.full.pdf+html}, interhash = {c5bfd473bc95108f0f169e2276741f50}, intrahash = {45660159ba36ce8d636afaa802725f3e}, journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences}, month = mar, number = 1987, title = {Augmented intelligence: the Web and human intelligence}, url = {http://rsta.royalsocietypublishing.org/content/371/1987/20120383.short}, volume = 371, year = 2013 } @article{robertson2013programming, abstract = {The aim of ‘programming the global computer’ was identified by Milner and others as one of the grand challenges of computing research. At the time this phrase was coined, it was natural to assume that this objective might be achieved primarily through extending programming and specification languages. The Internet, however, has brought with it a different style of computation that (although harnessing variants of traditional programming languages) operates in a style different to those with which we are familiar. The ‘computer’ on which we are running these computations is a social computer in the sense that many of the elementary functions of the computations it runs are performed by humans, and successful execution of a program often depends on properties of the human society over which the program operates. These sorts of programs are not programmed in a traditional way and may have to be understood in a way that is different from the traditional view of programming. This shift in perspective raises new challenges for the science of the Web and for computing in general.}, author = {Robertson, David and Giunchiglia, Fausto}, doi = {10.1098/rsta.2012.0379}, eprint = {http://rsta.royalsocietypublishing.org/content/371/1987/20120379.full.pdf+html}, interhash = {c671d953e4eb09fc3fe67f93ccd2024c}, intrahash = {a802922683b23455f903551ee2b24b42}, journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences}, month = mar, number = 1987, title = {Programming the social computer}, url = {http://rsta.royalsocietypublishing.org/content/371/1987/20120379.abstract}, volume = 371, year = 2013 } @article{maisonneuve2010participatory, abstract = {Noise pollution is a major problem in cities around the world. The current methods to assess it neglect to represent the real exposure experienced by the citizens themselves, and therefore could lead to wrong conclusions and a biased representations. In this paper we present a novel approach to monitor noise pollution involving the general public. Using their mobile phones as noise sensors, we provide a low cost solution for the citizens to measure their personal exposure to noise in their everyday environment and participate in the creation of collective noise maps by sharing their geo-localized and annotated measurements with the community. Our prototype, called NoiseTube, can be found online [1].}, author = {Maisonneuve, Nicolas and Stevens, Matthias and Ochab, Bartek}, doi = {10.3233/IP-2010-0200}, interhash = {75f1760b3c55de573fffd69fcc10548e}, intrahash = {4dbb1ce355b7249bc2f66ed4b2126bab}, journal = {Information Polity}, month = jan, number = 1, pages = {51--71}, publisher = {IOS Press}, title = {Participatory noise pollution monitoring using mobile phones}, url = {http://dx.doi.org/10.3233/IP-2010-0200}, volume = 15, year = 2010 } @article{kanjo2010noisespy, abstract = {In this paper we present the design, implementation, evaluation, and user experiences of the NoiseSpy application, our sound sensing system that turns the mobile phone into a low-cost data logger for monitoring environmental noise. It allows users to explore a city area while collaboratively visualizing noise levels in real-time. The software combines the sound levels with GPS data in order to generate a map of sound levels that were encountered during a journey. We report early findings from the trials which have been carried out by cycling couriers who were given Nokia mobile phones equipped with the NoiseSpy software to collect noise data around Cambridge city. Indications are that, not only is the functionality of this personal environmental sensing tool engaging for users, but aspects such as personalization of data, contextual information, and reflection upon both the data and its collection, are important factors in obtaining and retaining their interest.}, acmid = {1831011}, address = {Hingham, MA, USA}, author = {Kanjo, Eiman}, doi = {10.1007/s11036-009-0217-y}, interhash = {12b29df257d71dfd37193d6b4665004e}, intrahash = {387ebc6472794f598d07256a45f3d9b7}, issn = {1383-469X}, issue_date = {August 2010}, journal = {Mobile Networks and Applications}, month = aug, number = 4, numpages = {13}, pages = {562--574}, publisher = {Kluwer Academic Publishers}, title = {NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping}, url = {http://dx.doi.org/10.1007/s11036-009-0217-y}, volume = 15, year = 2010 } @inproceedings{liddo2010cohere, abstract = {This paper presents the rationale for treating Contested Collective Intelligence (CCI) as a significant and distinctive dimension of the broader Collective Intelligence design space for organizations. CCI is contrasted with other forms of CI, and building on research in sensemaking, and the modeling of dialogue and debate, we motivate a set of requirements for an ideal CCI platform. We then describe a social, semantic annotation tool called Cohere, which serves as our working prototype of the CCI concept, now being deployed in several communities.}, author = {Liddo, Anna De and Shum, Simon Buckingham}, booktitle = {ACM Computer Supported Cooperative Work (CSCW 2010) - Workshop: Collective Intelligence In Organizations - Toward a Research Agenda}, interhash = {4543ef44021cb9bc6f11cf025e36d5a6}, intrahash = {8573225cb6eeb7e1b32f4a951af8a5b5}, month = feb, title = {Cohere: A prototype for contested collective intelligence}, url = {http://oro.open.ac.uk/19554/}, year = 2010 } @incollection{calemis2010astra, abstract = {Awareness systems are a class of computer mediated communication systems that help individuals or groups build and maintain a peripheral awareness of each other. Awareness systems for informal social use are still in their infancy as a technology and as a research area. Such systems promise to address pressing social problems: elderly living alone, families living apart for large parts of the working week, monitoring the well being of an ill relative, etc. The ASTRA platform, which is being developed in the context of the EU research project ASTRA, provides a generalized solution to the development of awareness applications that are based on the concept of pervasive awareness. In this paper, we shall present how smart objects in a person’s environment can be used to capture and convey awareness information under this person’s control.}, author = {Calemis, Ioannis and Kameas, Achilles and Goumopoulos, Christos and Berg, Erik}, booktitle = {Innovations and Advances in Computer Sciences and Engineering}, doi = {10.1007/978-90-481-3658-2_32}, editor = {Sobh, Tarek}, interhash = {3567aedc104bf4036ed4b5be72d06b65}, intrahash = {1274b00c06c3b923a2c46a2c79587923}, isbn = {978-90-481-3657-5}, language = {English}, pages = {185--190}, publisher = {Springer Netherlands}, title = {ASTRA: An Awareness Connectivity Platform for Designing Pervasive Awareness Applications}, url = {http://dx.doi.org/10.1007/978-90-481-3658-2_32}, year = 2010 } @inproceedings{derose2008building, abstract = {The rapid growth of Web communities has motivated many solutions for building community data portals. These solutions follow roughly two approaches. The first approach (e.g., Libra, Citeseer, Cimple) employs semi-automatic methods to extract and integrate data from a multitude of data sources. The second approach (e.g., Wikipedia, Intellipedia) deploys an initial portal in wiki format, then invites community members to revise and add material. In this paper we consider combining the above two approaches to building community portals. The new hybrid machine-human approach brings significant benefits. It can achieve broader and deeper coverage, provide more incentives for users to contribute, and keep the portal more up-to-date with less user effort. In a sense, it enables building "community wikipedias", backed by an underlying structured database that is continuously updated using automatic techniques. We outline our ideas for the new approach, describe its challenges and opportunities, and provide initial solutions. Finally, we describe a real-world implementation and preliminary experiments that demonstrate the utility of the new approach.}, author = {DeRose, P. and Chai, Xiaoyong and Gao, B.J. and Shen, W. and Doan, An Hai and Bohannon, P. and Zhu, Xiaojin}, booktitle = {24th International Conference on Data Engineering}, doi = {10.1109/ICDE.2008.4497473}, interhash = {00f45357225b1e75ed93bddb8d456fb7}, intrahash = {38a2e84d3dfd845d9c260d5f15161c6f}, month = apr, pages = {646--655}, publisher = {IEEE}, title = {Building Community Wikipedias: A Machine-Human Partnership Approach}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4497473&tag=1}, year = 2008 } @inproceedings{chi2009augmented, abstract = {We are experiencing a new Social Web, where people share, communicate, commiserate, and conflict with each other. As evidenced by systems like Wikipedia, twitter, and delicious.com, these environments are turning people into social information foragers and sharers. Groups interact to resolve conflicts and jointly make sense of topic areas from "Obama vs. Clinton" to "Islam."
PARC's Augmented Social Cognition researchers -- who come from cognitive psychology, computer science, HCI, CSCW, and other disciplines -- focus on understanding how to "enhance a group of people's ability to remember, think, and reason". Through Social Web systems like social bookmarking sites, blogs, Wikis, and more, we can finally study, in detail, these types of enhancements on a very large scale.
Here we summarize recent work and early findings such as: (1) how conflict and coordination have played out in Wikipedia, and how social transparency might affect reader trust; (2) how decreasing interaction costs might change participation in social tagging systems; and (3) how computation can help organize user-generated content and metadata.}, acmid = {1559959}, address = {New York, NY, USA}, author = {Chi, Ed H.}, booktitle = {Proceedings of the 2009 ACM SIGMOD International Conference on Management of data}, doi = {10.1145/1559845.1559959}, interhash = {d24a64ce5e95bae4de9329a467342dee}, intrahash = {d09b484b1036ca8273743cac1992dd7f}, isbn = {978-1-60558-551-2}, location = {Providence, Rhode Island, USA}, numpages = {12}, pages = {973--984}, publisher = {ACM}, title = {Augmented social cognition: using social web technology to enhance the ability of groups to remember, think, and reason}, url = {http://doi.acm.org/10.1145/1559845.1559959}, year = 2009 } @article{liu2012crowdsourcing, abstract = {Some complex problems, such as image tagging and natural language processing, are very challenging for computers, where even state-of-the-art technology is yet able to provide satisfactory accuracy. Therefore, rather than relying solely on developing new and better algorithms to handle such tasks, we look to the crowdsourcing solution -- employing human participation -- to make good the shortfall in current technology. Crowdsourcing is a good supplement to many computer tasks. A complex job may be divided into computer-oriented tasks and human-oriented tasks, which are then assigned to machines and humans respectively.
To leverage the power of crowdsourcing, we design and implement a Crowdsourcing Data Analytics System, CDAS. CDAS is a framework designed to support the deployment of various crowdsourcing applications. The core part of CDAS is a quality-sensitive answering model, which guides the crowdsourcing engine to process and monitor the human tasks. In this paper, we introduce the principles of our quality-sensitive model. To satisfy user required accuracy, the model guides the crowdsourcing query engine for the design and processing of the corresponding crowdsourcing jobs. It provides an estimated accuracy for each generated result based on the human workers' historical performances. When verifying the quality of the result, the model employs an online strategy to reduce waiting time. To show the effectiveness of the model, we implement and deploy two analytics jobs on CDAS, a twitter sentiment analytics job and an image tagging job. We use real Twitter and Flickr data as our queries respectively. We compare our approaches with state-of-the-art classification and image annotation techniques. The results show that the human-assisted methods can indeed achieve a much higher accuracy. By embedding the quality-sensitive model into crowdsourcing query engine, we effectively reduce the processing cost while maintaining the required query answer quality.}, acmid = {2336676}, author = {Liu, Xuan and Lu, Meiyu and Ooi, Beng Chin and Shen, Yanyan and Wu, Sai and Zhang, Meihui}, interhash = {41ad6e73b03373d76d3164ba248335d7}, intrahash = {2091967734f96c4afbc09319d48a8c65}, issn = {2150-8097}, issue_date = {June 2012}, journal = {Proceedings of the VLDB Endowment}, month = jun, number = 10, numpages = {12}, pages = {1040--1051}, publisher = {VLDB Endowment}, title = {CDAS: a crowdsourcing data analytics system}, url = {http://dl.acm.org/citation.cfm?id=2336664.2336676}, volume = 5, year = 2012 } @inproceedings{jeffery2008payasyougo, abstract = {A primary challenge to large-scale data integration is creating semantic equivalences between elements from different data sources that correspond to the same real-world entity or concept. Dataspaces propose a pay-as-you-go approach: automated mechanisms such as schema matching and reference reconciliation provide initial correspondences, termed candidate matches, and then user feedback is used to incrementally confirm these matches. The key to this approach is to determine in what order to solicit user feedback for confirming candidate matches.
In this paper, we develop a decision-theoretic framework for ordering candidate matches for user confirmation using the concept of the value of perfect information (VPI). At the core of this concept is a utility function that quantifies the desirability of a given state; thus, we devise a utility function for dataspaces based on query result quality. We show in practice how to efficiently apply VPI in concert with this utility function to order user confirmations. A detailed experimental evaluation on both real and synthetic datasets shows that the ordering of user feedback produced by this VPI-based approach yields a dataspace with a significantly higher utility than a wide range of other ordering strategies. Finally, we outline the design of Roomba, a system that utilizes this decision-theoretic framework to guide a dataspace in soliciting user feedback in a pay-as-you-go manner.}, acmid = {1376701}, address = {New York, NY, USA}, author = {Jeffery, Shawn R. and Franklin, Michael J. and Halevy, Alon Y.}, booktitle = {Proceedings of the 2008 ACM SIGMOD international conference on Management of data}, doi = {10.1145/1376616.1376701}, interhash = {3ceaf563712b776c1ed97a8cb061f63b}, intrahash = {3bff24fb9eb1e39fa97a524aabb8dee9}, isbn = {978-1-60558-102-6}, location = {Vancouver, Canada}, numpages = {14}, pages = {847--860}, publisher = {ACM}, title = {Pay-as-you-go user feedback for dataspace systems}, url = {http://doi.acm.org/10.1145/1376616.1376701}, year = 2008 } @mastersthesis{olson2012cloud, abstract = {My thesis describes the design and implementation of systems that empower individuals to help their communities respond to critical situations and to participate in research that helps them understand and improve their environments. People want to help their communities respond to threats such as earthquakes, wildfires, mudslides and hurricanes, and they want to participate in research that helps them understand and improve their environment. “Citizen Science” projects that facilitate this interaction include projects that monitor climate change, water quality and animal habitats. My thesis explores the design and analysis of community-based sense and response systems that enable individuals to participate in critical community activities and scientific research that monitors their environments.}, author = {Olson, Michael J.}, interhash = {a9cdee464e76cd5210c13d7f66981e83}, intrahash = {d9e22a1a5e9404a805aee5cb0fd406c4}, school = {California Institute of Technology}, title = {Cloud computing for citizen science}, type = {Master's thesis}, url = {http://resolver.caltech.edu/CaltechTHESIS:08232011-122341638}, year = 2012 } @article{raykar2010learning, abstract = {For many supervised learning tasks it may be infeasible (or very expensive) to obtain objective and reliable labels. Instead, we can collect subjective (possibly noisy) labels from multiple experts or annotators. In practice, there is a substantial amount of disagreement among the annotators, and hence it is of great practical interest to address conventional supervised learning problems in this scenario. In this paper we describe a probabilistic approach for supervised learning when we have multiple annotators providing (possibly noisy) labels but no absolute gold standard. The proposed algorithm evaluates the different experts and also gives an estimate of the actual hidden labels. Experimental results indicate that the proposed method is superior to the commonly used majority voting baseline.}, acmid = {1859894}, author = {Raykar, Vikas C. and Yu, Shipeng and Zhao, Linda H. and Valadez, Gerardo Hermosillo and Florin, Charles and Bogoni, Luca and Moy, Linda}, interhash = {8113daf47997fddf48e4c6c79f2eba56}, intrahash = {14220abe8babfab01c0cdd5ebd5e4b7c}, issn = {1532-4435}, issue_date = {3/1/2010}, journal = {Journal of Machine Learning Research}, month = aug, numpages = {26}, pages = {1297--1322}, publisher = {JMLR.org}, title = {Learning From Crowds}, url = {http://dl.acm.org/citation.cfm?id=1756006.1859894}, volume = 11, year = 2010 } @incollection{li2011incorporating, abstract = {In scientific cooperation network, ambiguous author names may occur due to the existence of multiple authors with the same name. Users of these networks usually want to know the exact author of a paper, whereas we do not have any unique identifier to distinguish them. In this paper, we focus ourselves on such problem, we propose a new method that incorporates user feedback into the model for name disambiguation of scientific cooperation network. Perceptron is used as the classifier. Two features and a constraint drawn from user feedback are incorporated into the perceptron to enhance the performance of name disambiguation. Specifically, we construct user feedback as a training stream, and refine the perceptron continuously. Experimental results show that the proposed algorithm can learn continuously and significantly outperforms the previous methods without introducing user interactions.}, address = {Berlin/Heidelberg}, affiliation = {Intelligent and Distributed Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074 P.R. China}, author = {Li, Yuhua and Wen, Aiming and Lin, Quan and Li, Ruixuan and Lu, Zhengding}, booktitle = {Web-Age Information Management}, doi = {10.1007/978-3-642-23535-1_39}, editor = {Wang, Haixun and Li, Shijun and Oyama, Satoshi and Hu, Xiaohua and Qian, Tieyun}, interhash = {3baace12cb4481dcceb53c2d47f413b5}, intrahash = {96f2ae8551126527c2dfe69c8fa22f6c}, isbn = {978-3-642-23534-4}, keyword = {Computer Science}, pages = {454--466}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Incorporating User Feedback into Name Disambiguation of Scientific Cooperation Network}, url = {http://dx.doi.org/10.1007/978-3-642-23535-1_39}, volume = 6897, year = 2011 } @article{lofi2012information, abstract = {Recent years brought tremendous advancements in the area of automated information extraction. But still, problem scenarios remain where even state-of-the-art algorithms do not provide a satisfying solution. In these cases, another aspiring recent trend can be exploited to achieve the required extraction quality: explicit crowdsourcing of human intelligence tasks. In this paper, we discuss the synergies between information extraction and crowdsourcing. In particular, we methodically identify and classify the challenges and fallacies that arise when combining both approaches. Furthermore, we argue that for harnessing the full potential of either approach, true hybrid techniques must be considered. To demonstrate this point, we showcase such a hybrid technique, which tightly interweaves information extraction with crowdsourcing and machine learning to vastly surpass the abilities of either technique.}, address = {Berlin/Heidelberg}, affiliation = {Institut für Informationssysteme, Technische Universität Braunschweig, Braunschweig, Germany}, author = {Lofi, Christoph and Selke, Joachim and Balke, Wolf-Tilo}, doi = {10.1007/s13222-012-0092-8}, interhash = {941feeaa7bb134e0a5f8b5c0225756b8}, intrahash = {37cc8f1d19105a073544d6594fbbc033}, issn = {1618-2162}, journal = {Datenbank-Spektrum}, keyword = {Computer Science}, number = 2, pages = {109--120}, publisher = {Springer}, title = {Information Extraction Meets Crowdsourcing: A Promising Couple}, url = {http://dx.doi.org/10.1007/s13222-012-0092-8}, volume = 12, year = 2012 } @inproceedings{paton2011feedback, abstract = {User feedback is gaining momentum as a means of addressing the difficulties underlying information integration tasks. It can be used to assist users in building information integration systems and to improve the quality of existing systems, e.g., in dataspaces. Existing proposals in the area are confined to specific integration sub-problems considering a specific kind of feedback sought, in most cases, from a single user. We argue in this paper that, in order to maximize the benefits that can be drawn from user feedback, it should be considered and managed as a first class citizen. Accordingly, we present generic operations that underpin the management of feedback within information integration systems, and that are applicable to feedback of different kinds, potentially supplied by multiple users with different expectations. We present preliminary solutions that can be adopted for realizing such operations, and sketch a research agenda for the information integration community.}, author = {Paton, Norman W. and Fernandes, Alvaro A. A. and Hedeler, Cornelia and Embury, Suzanne M.}, booktitle = {Proceedings of the Conference on Innovative Data Systems Research (CIDR)}, interhash = {1874e5c09919244808457021d2d884d1}, intrahash = {cd75210156615616e4f25c91143040c4}, pages = {175--183}, title = {User Feedback as a First Class Citizen in Information Integration Systems}, url = {http://www.cidrdb.org/cidr2011/Papers/CIDR11_Paper21.pdf}, year = 2011 } @inproceedings{chai2009efficiently, abstract = {Many applications increasingly employ information extraction and integration (IE/II) programs to infer structures from unstructured data. Automatic IE/II are inherently imprecise. Hence such programs often make many IE/II mistakes, and thus can significantly benefit from user feedback. Today, however, there is no good way to automatically provide and process such feedback. When finding an IE/II mistake, users often must alert the developer team (e.g., via email or Web form) about the mistake, and then wait for the team to manually examine the program internals to locate and fix the mistake, a slow, error-prone, and frustrating process.
In this paper we propose a solution for users to directly provide feedback and for IE/II programs to automatically process such feedback. In our solution a developer U uses hlog, a declarative IE/II language, to write an IE/II program P. Next, U writes declarative user feedback rules that specify which parts of P's data (e.g., input, intermediate, or output data) users can edit, and via which user interfaces. Next, the so-augmented program P is executed, then enters a loop of waiting for and incorporating user feedback. Given user feedback F on a data portion of P, we show how to automatically propagate F to the rest of P, and to seamlessly combine F with prior user feedback. We describe the syntax and semantics of hlog, a baseline execution strategy, and then various optimization techniques. Finally, we describe experiments with real-world data that demonstrate the promise of our solution.}, acmid = {1559857}, address = {New York, NY, USA}, author = {Chai, Xiaoyong and Vuong, Ba-Quy and Doan, AnHai and Naughton, Jeffrey F.}, booktitle = {Proceedings of the 35th SIGMOD international conference on Management of data}, doi = {10.1145/1559845.1559857}, interhash = {5860215447e374b059597c0e3864e388}, intrahash = {d6c9fbf442a935dc0618107f8fb54d44}, isbn = {978-1-60558-551-2}, location = {Providence, Rhode Island, USA}, numpages = {14}, pages = {87--100}, publisher = {ACM}, title = {Efficiently incorporating user feedback into information extraction and integration programs}, url = {http://doi.acm.org/10.1145/1559845.1559857}, year = 2009 } @inproceedings{marcus2011crowdsourced, abstract = {Amazon's Mechanical Turk (\MTurk") service allows users to post short tasks (\HITs") that other users can receive a small amount of money for completing. Common tasks on the system include labelling a collection of images, com- bining two sets of images to identify people which appear in both, or extracting sentiment from a corpus of text snippets. Designing a work ow of various kinds of HITs for ltering, aggregating, sorting, and joining data sources together is common, and comes with a set of challenges in optimizing the cost per HIT, the overall time to task completion, and the accuracy of MTurk results. We propose Qurk, a novel query system for managing these work ows, allowing crowd- powered processing of relational databases. We describe a number of query execution and optimization challenges, and discuss some potential solutions.}, author = {Marcus, Adam and Wu, Eugene and Madden, Samuel and Miller, Robert C.}, booktitle = {Proceedings of the 5th Biennial Conference on Innovative Data Systems Research}, doi = {1721.1/62827}, interhash = {b6b7d67c3c09259fb2d5df3f52e24c9d}, intrahash = {29723ba38aa6039091769cd2f69a1514}, month = jan, pages = {211--214}, publisher = {CIDR}, title = {Crowdsourced Databases: Query Processing with People}, url = {http://dspace.mit.edu/handle/1721.1/62827}, year = 2011 } @inproceedings{franklin2011crowddb, abstract = {Some queries cannot be answered by machines only. Processing such queries requires human input for providing information that is missing from the database, for performing computationally difficult functions, and for matching, ranking, or aggregating results based on fuzzy criteria. CrowdDB uses human input via crowdsourcing to process queries that neither database systems nor search engines can adequately answer. It uses SQL both as a language for posing complex queries and as a way to model data. While CrowdDB leverages many aspects of traditional database systems, there are also important differences. Conceptually, a major change is that the traditional closed-world assumption for query processing does not hold for human input. From an implementation perspective, human-oriented query operators are needed to solicit, integrate and cleanse crowdsourced data. Furthermore, performance and cost depend on a number of new factors including worker affinity, training, fatigue, motivation and location. We describe the design of CrowdDB, report on an initial set of experiments using Amazon Mechanical Turk, and outline important avenues for future work in the development of crowdsourced query processing systems.}, acmid = {1989331}, address = {New York, NY, USA}, author = {Franklin, Michael J. and Kossmann, Donald and Kraska, Tim and Ramesh, Sukriti and Xin, Reynold}, booktitle = {Proceedings of the 2011 international conference on Management of data}, doi = {10.1145/1989323.1989331}, interhash = {8a3f1b0fb94083c918960f1e756fe496}, intrahash = {9525ebea13b41f27a49bafcf2f1132c6}, isbn = {978-1-4503-0661-4}, location = {Athens, Greece}, numpages = {12}, pages = {61--72}, publisher = {ACM}, title = {CrowdDB: answering queries with crowdsourcing}, url = {http://doi.acm.org/10.1145/1989323.1989331}, year = 2011 } @inproceedings{yuen2009survey, abstract = {Human computation is a technique that makes use of human abilities for computation to solve problems. The human computation problems are the problems those computers are not good at solving but are trivial for humans. In this paper, we give a survey of various human computation systems which are categorized into initiatory human computation, distributed human computation and social game-based human computation with volunteers, paid engineers and online players. For the existing large number of social games, some previous works defined various types of social games, but the recent developed social games cannot be categorized based on the previous works. In this paper, we define the categories and the characteristics of social games which are suitable for all existing ones. Besides, we present a survey on the performance aspects of human computation system. This paper gives a better understanding on human computation system.}, author = {Yuen, Man-Ching and Chen, Ling-Jyh and King, I.}, booktitle = {Proceedings of the International Conference on Computational Science and Engineering, CSE '09}, doi = {10.1109/CSE.2009.395}, interhash = {69f9bd3e6a721f226e39e1f990e20286}, intrahash = {8670a20dbf6aa9dd21da81ab78a1e333}, month = aug, pages = {723--728}, title = {A Survey of Human Computation Systems}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5283450&tag=1}, volume = 4, year = 2009 } @inproceedings{chan2009mathematical, abstract = {Human computation is a technique that makes use of human abilities for computation to solve problems. Social games use the power of the Internet game players to solve human computation problems. In previous works, many social games were proposed and were quite successful, but no formal framework exists for designing social games in general. A formal framework is important because it lists out the design elements of a social game, the characteristics of a human computation problem, and their relationships. With a formal framework, it simplifies the way to design a social game for a specific problem. In this paper, our contributions are: (1) formulate a formal model on social games, (2) analyze the framework and derive some interesting properties based on model's interactions, (3) illustrate how some current social games can be realized with the proposed formal model, and (4) describe how to design a social game for solving a specific problem with the use of the proposed formal model. This paper presents a set of design guidelines derived from the formal model and demonstrates that the model can help to design a social game for solving a specific problem in a formal and structural way.}, author = {Chan, Kam Tong and King, I. and Yuen, Man-Ching}, booktitle = {Proceedings of the International Conference on Computational Science and Engineering, CSE '09}, doi = {10.1109/CSE.2009.166}, interhash = {a54732b662bcb0d763139a38f6525b56}, intrahash = {216d582316e970eb498423ee8448edbe}, month = aug, pages = {1205--1210}, title = {Mathematical Modeling of Social Games}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5283086&tag=1}, volume = 4, year = 2009 }