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2024-01-26
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How do people feel about AI?
A nationally representative survey of public attitudes to artificial intelligence in Britain
Ada Lovelace Institute
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2021-05-25
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Commercial Visual Analytics Systems - Advances in the Big Data Analytics Field
Five years after the first state-of-the-art report on Commercial Visual Analytics Systems we present a reevaluation of the Big Data Analytics field. We build on the success of the 2012 survey, which was influential even beyond the boundaries of the InfoVis and Visual Analytics (VA) community. While the field has matured significantly since the original survey, we find that innovation and research-driven development are increasingly sacrificed to satisfy a wide range of user groups. We evaluate new product versions on established evaluation criteria, such as available features, performance, and usability, to extend on and assure comparability with the previous survey. We also investigate previously unavailable products to paint a more complete picture of the commercial VA landscape. Furthermore, we introduce novel measures, like suitability for specific user groups and the ability to handle complex data types, and undertake a new case study to highlight innovative features. We explore the achievements in the commercial sector in addressing VA challenges and propose novel developments that should be on systems’ roadmaps in the coming years.
Michael Behrisch, Dirk Streeb, Florian Stoffel, Daniel Seebacher, Brian MatejekStefan Hagen Weber, Sebastian Mittelst ̈adt, Hanspeter Pfister, Daniel Keim
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2011-04-18
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Advances in Collaborative Filtering
The collaborative filtering (CF) approach to recommenders has recently enjoyed much interest and progress. The fact that it played a central role within the recently
completed Netflix competition has contributed to its popularity. This chapter surveys the recent progress in the field. Matrix factorization techniques, which became a first choice for implementing CF, are described together with recent innovations. We also describe several extensions that bring competitive accuracy into neighborhood methods, which used to dominate the field. The chapter demonstrates how to utilize temporal models and implicit feedback to extend models accuracy. In passing, we include detailed descriptions of some the central methods developed for tackling the challenge of the Netflix Prize competition.
Yehuda Koren and Robert Bell
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2010-12-14
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Privacy-preserving data publishing: A survey of recent developments
The collection of digital information by governments, corporations, and individuals has created tremendous opportunities for knowledge- and information-based decision making. Driven by mutual benefits, or by regulations that require certain data to be published, there is a demand for the exchange and publication of data among various parties. Data in its original form, however, typically contains sensitive information about individuals, and publishing such data will violate individual privacy. The current practice in data publishing relies mainly on policies and guidelines as to what types of data can be published and on agreements on the use of published data. This approach alone may lead to excessive data distortion or insufficient protection. Privacy-preserving data publishing (PPDP) provides methods and tools for publishing useful information while preserving data privacy. Recently, PPDP has received considerable attention in research communities, and many approaches have been proposed for different data publishing scenarios. In this survey, we will systematically summarize and evaluate different approaches to PPDP, study the challenges in practical data publishing, clarify the differences and requirements that distinguish PPDP from other related problems, and propose future research directions.
B. Fung, K. Wang, R. Chen, P. S. Yu
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2010-05-28
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The Fate of the Semantic Web
Technology experts and stakeholders who participated in a recent survey believe online information will continue to be organized and made accessible in smarter and more useful ways in coming years.
Pew Research Center's Internet & American Life Project
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2007-12-03
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Information Gathering in the Electronic Age: The Hidden Cost of the Hunt
