Hierarchical Aggregation for Reputation Feedback of Services Networks

Product ratings are popular tools to support buying decisions of consumers, which are also valuable for online retailers. In online marketplaces, vendors can use rating systems to build trust and reputation. To build trust, it is really important to evaluate the aggregate score for an item or a service. An accurate aggregation of ratings can embody the true quality of offerings, which is not only beneficial for providers in adjusting operation and sales tactics, but also helpful for consumers in discovery and purchase decisions. In this paper, we propose a hierarchical aggregation model for reputation feedback, where the state-of-the-art feature-based matrix factorization models are used. We first present our motivation. Then, we propose feature-based matrix factorization models. Finally, we address how to utilize the above modes to formulate the hierarchical aggregation model. Through a set of experiments, we can get that the aggregate score calculated by our model is greater than the corresponding value obtained by the state-of-the-art IRURe; i.e., the outputs of our models can better match the true rank orders.

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An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-11-2016-0340 ◽

2017 ◽

Vol 44 (4) ◽

pp. 428-441 ◽

Cited By ~ 11

Author(s):

Michał R. Nowicki ◽

Dominik Belter ◽

Aleksander Kostusiak ◽

Petr Cížek ◽

Jan Faigl ◽

...

Keyword(s):

Performance Metrics ◽

State Of The Art ◽

Building Blocks ◽

Bundle Adjustment ◽

The State ◽

Legged Robots ◽

Evaluation Methodology ◽

Walking Robots ◽

Content Type ◽

Feature Based

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

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An Overview and Evaluation of the Cat Market Design Competition

10.1093/oxfordhb/9780199844371.013.18 ◽

2018 ◽

Author(s):

Tim Miller ◽

Jinzhong Niu ◽

Martin Chapman ◽

Peter McBurney

Keyword(s):

Computer Science ◽

Mechanism Design ◽

State Of The Art ◽

Market Design ◽

The State ◽

Online Commerce ◽

Competitive Environments ◽

Online Marketplaces ◽

Design Competition ◽

History Of

The rise of online commerce has led to an emerging discipline at the intersection of economics and computer science, a discipline which studies the properties and dynamics of automated trading in online marketplaces. The CAT Market Design Tournament was created to promote research into the design and deployment of economic mechanisms for such online marketplaces, particularly mechanisms able to adapt automatically to dynamic competitive environments. This research competition, which ran from 2007 to 2011), was won by four different teams and had entrants from thirteen countries. This chapter describes the motivation and history of the tournament and presents research that has arisen from it. The winners were experimentally “played off” to evaluate whether the state of the art in automated mechanism design improved during the CAT competition. The results show a clear and consistent improvement, supporting the belief that the competition has encouraged research in the field.

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Efficient Noisy Sound-Event Mixture Classification Using Adaptive-Sparse Complex-Valued Matrix Factorization and OvsO SVM

Sensors ◽

10.3390/s20164368 ◽

2020 ◽

Vol 20 (16) ◽

pp. 4368 ◽

Cited By ~ 1

Author(s):

Phetcharat Parathai ◽

Naruephorn Tengtrairat ◽

Wai Lok Woo ◽

Mohammed A. M. Abdullah ◽

Gholamreza Rafiee ◽

...

Keyword(s):

Matrix Factorization ◽

Single Channel ◽

State Of The Art ◽

Nonnegative Matrix ◽

The State ◽

Support Vector ◽

Zero Crossing ◽

Time Frequency ◽

Sound Event ◽

Short Time

This paper proposes a solution for events classification from a sole noisy mixture that consist of two major steps: a sound-event separation and a sound-event classification. The traditional complex nonnegative matrix factorization (CMF) is extended by cooperation with the optimal adaptive L1 sparsity to decompose a noisy single-channel mixture. The proposed adaptive L1 sparsity CMF algorithm encodes the spectra pattern and estimates the phase of the original signals in time-frequency representation. Their features enhance the temporal decomposition process efficiently. The support vector machine (SVM) based one versus one (OvsO) strategy was applied with a mean supervector to categorize the demixed sound into the matching sound-event class. The first step of the multi-class MSVM method is to segment the separated signal into blocks by sliding demixed signals, then encoding the three features of each block. Mel frequency cepstral coefficients, short-time energy, and short-time zero-crossing rate are learned with multi sound-event classes by the SVM based OvsO method. The mean supervector is encoded from the obtained features. The proposed method has been evaluated with both separation and classification scenarios using real-world single recorded signals and compared with the state-of-the-art separation method. Experimental results confirmed that the proposed method outperformed the state-of-the-art methods.

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Practical Picture Processing

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100051700 ◽

1974 ◽

Vol 32 ◽

pp. 338-339

Author(s):

T. A. Welton

Keyword(s):

Radiation Damage ◽

Coherence Length ◽

Spatial Information ◽

State Of The Art ◽

Coherent Radiation ◽

The State ◽

Energy Spread ◽

Electron Micrograph ◽

Picture Processing ◽

Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

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