Improving the Quality of Online Search Services: On the Service Multi-selection Problem

2016 ◽  
Author(s):  
Yanik Ngoko ◽  
Christophe Cerin ◽  
Alfredo Goldman
Keyword(s):  
Selection Problem ◽  
Online Search

scholarly journals Does Online Search Improve the Match Quality of New Hires?

2021 ◽  
pp. 101981
Author(s):  
Nicole Gürtzgen ◽  
Benjamin Lochner ◽  
Laura Pohlan ◽  
Gerard J. van den Berg
Keyword(s):  
Online Search ◽  
Match Quality ◽  
New Hires

scholarly journals MANAGEMENT TECHNIQUES FOR IMPROVING THE QUALITY OF DECISION-MAKING BY OWNERS OF APARTMENT BUILDINGS ON THE CHOICE OF MANAGEMENT ORGANIZATION

2020 ◽  
pp. 104-111
Author(s):  
A. V. Demin ◽  
I. V. Rybalchenko ◽  
I. V. Milkina
Keyword(s):  
Decision Making ◽  
Selection Criteria ◽  
Selection Problem ◽  
Economic Losses ◽  
Apartment Building ◽  
Apartment Buildings ◽  
Limited Applicability ◽  
Management Techniques ◽  
New System

The procedure for choosing the organization managing the apartment building is regulated in detail by legislation. However, the law, formally conforming to market principles, leaves the owners of residential premises in the house without any reasonable selection criteria. The wrong choice of a management company is fraught not only with economic losses, but also with safe living. At the same time, the ratings proposed for state accounting or statistics cannot be applied by owners to select the best candidate, since they have other goals. The limited applicability of these ratings and criteria systems has been argued in the article, and also well-grounded approaches and a new system of criteria necessary to resolve the selection problem have been proposed.

scholarly journals Optimal online algorithms for the portfolio selection problem, bi-directional trading and -search with interrelated prices

2019 ◽  
Vol 53 (2) ◽  
pp. 559-576 ◽  
Author(s):  
Pascal Schroeder ◽  
Imed Kacem ◽  
Günter Schmidt
Keyword(s):  
Portfolio Selection ◽  
Online Algorithms ◽  
Competitive Ratio ◽  
Numerical Experiments ◽  
Input Sequence ◽  
Relative Price ◽  
Selection Problem ◽  
Online Search ◽  
Worst Case ◽  
Portfolio Selection Problem

In this work we investigate the portfolio selection problem (P1) and bi-directional trading (P2) when prices are interrelated. Zhang et al. (J. Comb. Optim. 23 (2012) 159–166) provided the algorithm UND which solves one variant of P2. We are interested in solutions which are optimal from a worst-case perspective. For P1, we prove the worst-case input sequence and derive the algorithm optimal portfolio for interrelated prices (OPIP). We then prove the competitive ratio and optimality. We use the idea of OPIP to solve P2 and derive the algorithm called optimal conversion for interrelated prices (OCIP). Using OCIP, we also design optimal online algorithms for bi-directional search (P3) called bi-directional UND (BUND) and optimal online search for unknown relative price bounds (RUN). We run numerical experiments and conclude that OPIP and OCIP perform well compared to other algorithms even if prices do not behave adverse.

Optimizing Complex Service-Based Workflows for Stochastic QoS Parameters

2013 ◽  
Vol 10 (4) ◽  
pp. 1-38
Author(s):  
Dieter Schuller ◽  
Ulrich Lampe ◽  
Julian Eckert ◽  
Ralf Steinmetz ◽  
Stefan Schulte
Keyword(s):  
Quality Of Service ◽  
Service Selection ◽  
Case Analysis ◽  
Selection Problem ◽  
Worst Case Analysis ◽  
Average Case Analysis ◽  
Worst Case ◽  
Average Case ◽  
Qos Parameters

The challenge of optimally selecting services from a set of functionally appropriate ones under Quality of Service (QoS) constraints – the Service Selection Problem – has been extensively addressed in the literature based on deterministic parameters. In practice, however, Quality of Service QoS parameters rather follow a stochastic distribution. In the work at hand, we present an integrated approach which addresses the Service Selection Problem for complex structured as well as unstructured workflows in conjunction with stochastic Quality of Service parameters. Accounting for penalty cost which accrue due to Quality of Service violations, we perform a worst-case analysis as opposed to an average-case analysis aiming at avoiding additional penalties. Although considering conservative computations, QoS violations due to stochastic QoS behavior still may occur resulting in potentially severe penalties. Our proposed approach reduces this impact of stochastic QoS behavior on total cost significantly.

scholarly journals An Analysis of the Network Selection Problem for Heterogeneous Environments with User-Operator Joint Satisfaction and Multi-RAT Transmission

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
J. J. Escudero-Garzás ◽  
C. Bousoño-Calzón
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Heterogeneous Networks ◽  
Network Topology ◽  
Utility Functions ◽  
Selection Problem ◽  
Network Selection ◽  
Heterogeneous Environments ◽  
Radio Access

The trend in wireless networks is that several wireless radio access technologies (RATs) coexist in the same area, forming heterogeneous networks in which the users may connect to any of the available RATs. The problem of associating a user to the most suitable RAT, known as network selection problem (NSP), is of capital importance for the satisfaction of the users in these emerging environments. However, also the satisfaction of the operator is important in this scenario. In this work, we propose that a connection may be served by more than one RAT by using multi-RAT terminals. We formulate the NSP with multiple RAT association based on utility functions that take into consideration both user’s satisfaction and provider’s satisfaction. As users are characterized according to their expected quality of service, our results exhaustively analyze the influence of the user’s profile, along with the network topology and the type of applications served.

Information Entropy Selection Problem in a Number of Quality Analysis

2014 ◽  
Vol 556-562 ◽  
pp. 3730-3734
Author(s):  
Sun Tao ◽  
Peng Dong Du
Keyword(s):  
Relative Entropy ◽  
Information Entropy ◽  
Multiple Choice ◽  
Comparison Method ◽  
Selection Problem ◽  
Quality Analysis ◽  
Multiple Choice Questions

Multiple choice questions is one of the most widely used test, test after the effectiveness of each option subject judgment can provide an important reference for the evaluation of the quality of test. In this paper, by analyzing the multiple choice information entropy problem of multiple choice questions, given equal choice a formula to calculate the number of D. At the same time, the quality of the multiple choice questions the problems, gives the comparison method of using relative entropy.

scholarly journals Effect of feedback on the quality of suicide prevention websites: randomised controlled trial

2010 ◽  
Vol 197 (1) ◽  
pp. 73-74 ◽  
Author(s):  
Anthony F. Jorm ◽  
Julie-Anne Fischer ◽  
Elizabeth Oh
Keyword(s):  
Suicide Prevention ◽  
Mental Health Problems ◽  
Controlled Trial ◽  
The Internet ◽  
Consensus Guidelines ◽  
Online Search ◽  
Quality Of Information ◽  
Randomised Controlled ◽  
To Receive

SummaryThere is concern regarding the quality of information about mental health problems on the internet. A trial was carried out to see whether sending feedback to website administrators about the quality of information on their website would lead to an improvement (ACTRN12609000449235). Fifty-two suicide prevention websites were identified by means of an online search. The quality of information about how to help someone who is suicidal was scored against expert consensus guidelines. Websites were randomised to receive feedback or serve as controls. The information on the websites varied greatly in quality. However, feedback did not lead to an improvement.

A Service Selection Algorithm Based on Heterogeneous QoS Model and Synthetic Weights

2015 ◽  
Vol 734 ◽  
pp. 459-462 ◽  
Author(s):  
Sen Zeng ◽  
Guo Qi Ni ◽  
Miao Miao Fan ◽  
Lin Zhang ◽  
Yuan Hua He
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Selection Problem ◽  
Final Decision ◽  
Selection Algorithm ◽  
Decision Making Problem ◽  
Different Types ◽  
Traditional Service ◽  
Multi Attribute Decision Making

Quality of Service (QoS) aware-based service selection problem is a multi-attribute decision making problem. In order to solve service selection problem with QoS indicators describe by different types of data, a service selection algorithm based on heterogeneous QoS model and synthetic weight (SSAoHS) is proposed. SSAoHS introduces real number, interval number and linguistic data to describe different QoS attributes, considers the subjective and objective weights wholly, and makes the final decision referring to the expectation and variance of QoS attributes after computing the synthetic scores. SSAoHS expands the traditional service selection and it is efficient and effective.

Quality of health-related online search results

2014 ◽  
Vol 57 ◽  
pp. 454-462 ◽  
Author(s):  
Brent Kitchens ◽  
Christopher A. Harle ◽  
Shengli Li
Keyword(s):  
Online Search ◽  
Search Results ◽  
Health Related

scholarly journals The Quality of the Covariance Selection through Detection Problem and AUC Bounds

2017 ◽  
Author(s):  
Navid Tafaghodi khajavi ◽  
Anthony Kuh
Keyword(s):  
Model Selection ◽  
Selection Problem ◽  
Upper And Lower Bounds ◽  
Detection Problem ◽  
Covariance Selection ◽  
Kl Divergence ◽  
Model Distribution ◽  
Original Distribution ◽  
Model Selection Problem

This paper considers the problem of quantifying the quality of a model selection problem for a graphical model. The model selection problem often uses a distance measure such as the Kulback-Leibler (KL) distance to quantify the quality of the approximation between the original distribution and the model distribution. We extend this work by formulating the problem as a detection problem between the original distribution and the model distribution. In particular, we focus on the covariance selection problem by Dempster, [1], and consider the cases where the distributions are Gaussian distributions. Previous work showed that if the approximation model is a tree, that the optimal tree that minimizes the KL divergence can be found by using the Chow-Liu algorithm [2]. While the algorithm minimizes the KL divergence it does not minimize other measures such as other divergences and the area under the curve (AUC). These measures all depend on the eigenvalues of the correlation approximation measure (CAM). We find expressions for KL divergence, log-likelihood ratio, and AUC as a function of the CAM. Easily computable upper and lower bounds are also found for the AUC. The paper concludes by computing these measures for real and synthetic simulation data.

Sign in / Sign up

Export Citation Format

Share Document