24,294 research outputs found
Recommender Systems
The ongoing rapid expansion of the Internet greatly increases the necessity
of effective recommender systems for filtering the abundant information.
Extensive research for recommender systems is conducted by a broad range of
communities including social and computer scientists, physicists, and
interdisciplinary researchers. Despite substantial theoretical and practical
achievements, unification and comparison of different approaches are lacking,
which impedes further advances. In this article, we review recent developments
in recommender systems and discuss the major challenges. We compare and
evaluate available algorithms and examine their roles in the future
developments. In addition to algorithms, physical aspects are described to
illustrate macroscopic behavior of recommender systems. Potential impacts and
future directions are discussed. We emphasize that recommendation has a great
scientific depth and combines diverse research fields which makes it of
interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
Blindspot: Indistinguishable Anonymous Communications
Communication anonymity is a key requirement for individuals under targeted
surveillance. Practical anonymous communications also require
indistinguishability - an adversary should be unable to distinguish between
anonymised and non-anonymised traffic for a given user. We propose Blindspot, a
design for high-latency anonymous communications that offers
indistinguishability and unobservability under a (qualified) global active
adversary. Blindspot creates anonymous routes between sender-receiver pairs by
subliminally encoding messages within the pre-existing communication behaviour
of users within a social network. Specifically, the organic image sharing
behaviour of users. Thus channel bandwidth depends on the intensity of image
sharing behaviour of users along a route. A major challenge we successfully
overcome is that routing must be accomplished in the face of significant
restrictions - channel bandwidth is stochastic. We show that conventional
social network routing strategies do not work. To solve this problem, we
propose a novel routing algorithm. We evaluate Blindspot using a real-world
dataset. We find that it delivers reasonable results for applications requiring
low-volume unobservable communication.Comment: 13 Page
- …