Model Based Comparison of Discounted Cumulative Gain and Average Precision

In this paper, we propose to explain Discounted Cumulative Gain (DCG) as the expectation of the total utility collected by a user given a generative probabilistic model on how users browse the result page ranking list of a search engine. We contrast this with a generalization of Average Precision, pAP, that has been defined in Dupret and Piwowarski (2010) [13]. In both cases, user decision models coupled with Web search logs allow to estimate some parameters that are usually left to the designer of a metric. In this paper, we compare the user models for DCG and pAP at the interpretation and experimental level.DCG and AP are metrics computed before a ranking function is exposed to users and as such, their role is to predict the function performance. In counterpart to prognostic metric, a diagnostic metric is computed after observing the user interactions with the result list. A commonly used diagnostic metric is the clickthrough rate at position 1, for example. In this work we show that the same user model developed for DCG can be used to derive a diagnostic version of this metric. The same hold for pAP and any metric with a proper user model.We show that not only does this diagnostic view provide new information, it also allows to define a new criterion for assessing a metric. In previous works based on user decision modeling, the performance of different metrics were compared indirectly in terms of the ability of the associated user model to predict future user actions. Here we propose a new and more direct criterion based on the ability of the prognostic version of the metric to predict the diagnostic performance.     

Fixed points of weak contractions in cone metric spaces

Cone metric spaces are generalizations of metric spaces, where the metric is Banach space-valued. Weak contractions are generalizations of the Banach’s contraction mapping, which have been studied by several authors. In the present work, we establish a unique fixed point result for weak contractions in cone metric spaces. Our result is supported by an example.     

Note on Vector Translation with Respect to Thompson’s Metric

It is known that vector translations are contractive with respect to Thompson’s part metric. Here, we give a simple proof, based on a representation of Thompson’s metric through positive functionals. Moreover, we use contractivity of translations to prove a fixed point result for mappings that are Lipschitz continuous with respect to Thompson’s metric with Lipschitz constant r>1. The case r = 1 for order preserving or order reversing mappings has been recently studied by Lawson and Lim. We apply our result to a nonlinear boundary value problem.     

Almost sure convergence of random projected proximal and subgradient algorithms for distributed nonsmooth convex optimization

Two distributed algorithms are described that enable all users connected over a network to cooperatively solve the problem of minimizing the sum of all users’ objective functions over the intersection of all users’ constraint sets, where each user has its own private nonsmooth convex objective function and closed convex constraint set, which is the intersection of a number of simple, closed convex sets. One algorithm enables each user to adjust its estimate using the proximity operator of its objective function and the metric projection onto one constraint set randomly selected from a number of simple, closed convex sets. The other determines each user’s estimate using the subdifferential of its objective function instead of the proximity operator. Investigation of the two algorithms’ convergence properties for a diminishing step-size rule revealed that, under certain assumptions, the sequences of all users generated by each of the two algorithms converge almost surely to the same solution. It also showed that the rate of convergence depends on the step size and that a smaller step size results in quicker convergence. The results of numerical evaluation using a nonsmooth convex optimization problem support the convergence analysis and demonstrate the effectiveness of the two algorithms.     

Fuzzy optimization approach to component selection of fault-tolerant software system

In developing software systems, a manager’s goal is to design software using limited resources and meet the user requirements. One of the important user requirements concerns the reliability of the software. The decision to choose the right software modules (components) becomes extremely difficult because of the number of parameters to be considered while making the decision. If suitable components are not available, then the decision process is further complicated with build versus buy decisions. In this paper, we have formulated a fuzzy multi-objective approach to optimal decision “build-or-buy” for component selection for a fault-tolerant modular software system under the consensus recovery block scheme. A joint optimization model is formulated where the two objectives are maximization of system reliability and minimization of the system cost with a constraint on delivery time. An example of developing a retail system for small-and-medium-size enterprises is used to illustrate the proposed methodology.     

Stochastic optimization on social networks with application to service pricing

In this paper we develop a combined simulation and optimization approach for solving difficult decision problems on complex dynamic networks. For a specific reference problem we consider a telecommunication service provider who offers a telecommunication service to a market with network effects. More particularly, the service consumption of an individual user depends on both idiosyncratic characteristics and the popularity of this service among the customer’s immediate neighborhood. Both the social network and the individual user preferences are largely heterogeneous and changing over time. In addition the service provider’s decisions are made in absence of perfect knowledge about user preferences. The service provider pursues the strategy of stimulating the demand by offering differentiated prices to the customers. For finding the optimal pricing we apply a stochastic quasi-gradient algorithm that is integrated with a simulation model that drives the evolution of the network and user preferences over time. We show that exploiting the social network structure and implementing differentiated pricing can substantially increase the revenues of a service provider operating on a social network. More generally, we show that stochastic gradient methods represent a powerful methodology for the optimization of decisions in social networks.     

A variable metric Proximal-Descent Algorithm for monotone operators

In this paper, we discuss a variable metric Proximal-Descent Algorithm for finding a zero of any given maximal monotone operator. At each iteration, it first implements a proximal step and then a descent step to locate the new iterate. In the proximal step, we have replaced the regularization parameter by some positive definite matrix, which may vary from iteration to iteration. Under standard assumptions, we prove its global convergence without the matrix??s symmetry. Some key aspects of the algorithm??s applications are discussed. Preliminary numerical experiments show the efficiency in practical implementations.     

奇异值分解法在预测用户页面兴趣度中的应用

如何挖掘用户感兴趣的内容并向其推荐相应的产品是许多商务网站关注的重点。本文提出一个用户页面兴趣度公式,据此得到一个稀疏的页面兴趣度矩阵,考虑到矩阵的稀疏性会影响预测的准确性,我们首先用稀疏矩阵中每列非零元素的平均值对该列中值为零的元素进行修正,然后用奇异值分解法对原稀疏矩阵中值为零的元素进行再次修正,进而根据修正后的矩阵用SlopeOne算法对用户的页面兴趣度进行预测并用某网站的数据验证。结果表明:与稀疏矩阵相比,用修正后的矩阵预测的准确性有较大提高。     

Resource contention games in multiclass stochastic flow models

We consider resource contention games in a stochastic hybrid system setting using Stochastic Flow Models (SFM) with multiple classes and class-dependent objectives. We present a general modeling framework for such games, where Infinitesimal Perturbation Analysis (IPA) estimators are derived for the derivatives of various class-dependent objectives. This allows us to study these games from the point of view of system-centric optimization of a performance metric and compare it to the user-centric approach where each user optimizes its own performance metric. We derive explicit solutions for a specific model in which the competing user classes employ threshold control policies and service is provided on a First Come First Serve (FCFS) basis. The unbiasedness of the IPA estimators is established in this case and it is shown that under certain conditions the system-centric and user-centric optimization solutions coincide.     

A unifying model of strategic network formation

We provide a model that merges two basic models of strategic network formation and incorporates them as extreme cases: Jackson and Wolinsky’s connections model based on bilateral formation of links, and Bala and Goyal’s two-way flow model, where links can be unilaterally formed. In our model a link can be created unilaterally, but when it is only supported by one of the two players the flow through it suffers some friction or decay, but more than when it is supported by both players. When the friction in singly-supported links is maximal (i.e. there is no flow) we have Jackson and Wolinsky’s connections model, while when flow in singly-supported links is as good as in doubly-supported links we have Bala and Goyal’s two-way flow model. In this setting, a joint generalization of the results relative to efficiency and stability in both seminal papers is achieved, and the robustness in both models is tested with positive results.     

融合两阶段过程模型和改进Bass模型的网络社交平台上产品信息扩散研究

提出并验证了融合两阶段过程模型和改进Bass模型的网络社交平台上产品信息扩散模型。考虑用户转发动机构建产品信息扩散两阶段过程模型;考虑用户兴趣衰减效应改进Bass模型;融合这两个模型,考虑产品信息发布者明星效应、产品信息质量对产品信息扩散的影响,提出了产品信息扩散模型。以2019年11～12月新浪电影发布的电影预告片转发数据验证了所提模型,并与Bass模型进行了比较。结果表明,用户转发动机和用户兴趣衰减效应对产品信息扩散均有显著影响,所提模型的预测精度和拟合效果均优于Bass模型。所提模型可用于存在不同转发动机及具有衰减效应的其他信息转发量预测,尤其适合于在产品信息投放前期和早期对转发量的预测,是对信息扩散模型的补充。     

Common fixed point theorems in intuitionistic fuzzy metric spaces

The purpose of this paper, using the idea of intuitionistic fuzzy set due to Atanassov [2], we define the notion of intuitionistic fuzzy metric spaces (see, [1]) due to Kramosil and Michalek [17] and Jungck’s common fixed point theorem ([11]) is generalized to intuitionistic fuzzy metric spaces. Further, we first formulate the definition of weakly commuting and R-weakly commuting mappings in intuitionistic fuzzy metric spaces and prove the intuitionistic fuzzy version of Pant’s theorem ([21]).     

基于双层规划的高速公路收费费率优化模型

在全国联网收费的背景下,从动态收费的角度考虑,建立了双层规划模型,上层规划中将路网管理者作为领导者,以高速公路收费效益最大化为目标函数,同时考虑道路运营管理方的合理收益和养护成本支出情况,下层规划则以用户出行效用最大化为目标,充分考虑了道路使用者的道路选择差异性及道路拥堵对交通分布的影响,建立随机用户均衡模型.最后结合某地区AB地高速公路实际情况进行分析,采用了遗传模拟退火算法验证了模型的实用性,并与其他的算法对比,验证了算法的有效性。研究表明:优化模型可以有效提高高速公路的收费效益和用户的出行效用,可以分散高峰时的交通压力,提升高速公路的通行效率.     

Reputation,inequality and meeting techniques: visualising user hierarchy to support collaboration

Equality within groups is ordinarily taken for granted when technology for e-democracy is conceived and developed. However, inequality in online communication is just as common as in other social contexts. Therefore, we have developed a groupware with the express purpose of illuminating imbalance of power. Inequalities are measured and made visible to users of the system, and they change dynamically as actions are taken by users. The system is based on democratic meeting techniques and is reminiscent of a strategy game based on social media. Each participant’s score within the game is dynamically calculated and reflects that user’s activity, others’ reactions to that activity and reactions to others’ activities. The calculations and weighing mechanisms are open to inspection and change by the users, and hierarchical roles reflecting game levels may be attached to system rights belonging to individual users and user groups. The prototype we present stems from the question of how to conceive of groupware based on diversity and is the result of combining social theory with algorithms for modelling and visualising user hierarchy and status. Empirical user tests suggest improvements to the prototype’s interface, which will be implemented and further evaluated by embedding the algorithms in a system for e-participation.     

An interactive visual simulation system for industrial management

This paper describes a discrete event interactive simulation system which allows a user to watch the progress of a simulation model on a visual display terminal. The user may interact with the model in a flexible manner, in order to explore the consequence of alternative decisions or strategies. Output from the simulation may be directed, in an animated form, to a refresh display computer graphics screen, a black and white visual display unit or an intelligent colour visual display divice. The interactive system has been specifically designed to assist in decision making processes associated with industrial management problem situations.     

Environmentally friendly facility location with market competition

Many traditional facility location models assume spatial monopoly where market competition is ignored. Since facility locations affect the firm’s market exposure and subsequently its profit, accounting for the impact of the location decisions on customers while anticipating the reaction of competitor firms is essential. In this paper, we introduce a competitive facility location problem where market prices and production costs are determined through the economic equilibrium while explicitly considering competition from other firms. In order to accommodate for the growing efforts on limiting carbon emissions, the presented model includes constraints on the amount of carbon emissions that are due to transportation, while allowing carbon trading. The problem is formulated as a mixed integer non-linear model. Through numerical examples, we illustrate the effect of market competition on the location decisions and discuss the impact of emission limits and carbon trading on customers.     

Metrics and entropy for non-compact spaces

We investigate Bowen’s metric definition of topological entropy for homeomorphisms of non-compact spaces. Different equivalent metrics may assign to the homeomorphism different entropies. We show that the infimum of the metric entropies is greater than or equal to the supremum of the measure theoretic entropies. An example shows that it may be strictly greater. If the entropy of the homeomorphism can vary as the metrics vary we see that the supremum is infinity.     

The analyticity of a generalized Ruelle’s operator

In this work we propose a generalization of the concept of Ruelle’s operator for one dimensional lattices used in thermodynamic formalism and ergodic optimization, which we call generalized Ruelle’s operator. Our operator generalizes both the Ruelle operator proposed in [2] and the Perron Frobenius operator defined in [7]. We suppose the alphabet is given by a compact metric space, and consider a general a-priori measure to define the operator. We also consider the case where the set of symbols that can follow a given symbol of the alphabet depends on such symbol, which is an extension of the original concept of transition matrices from the theory of subshifts of finite type. We prove the analyticity of the Ruelle’s operator and present some examples.     

New cone fixed point theorems for nonlinear multivalued maps with their applications

In this paper, we first establish some new types of fixed point theorems for nonlinear multivalued maps in cone metric spaces. From those results, we obtain new fixed point theorems for nonlinear multivalued maps in metric spaces and the generalizations of Mizoguchi–Takahashi’s fixed point theorem and Berinde–Berinde’s fixed point theorem. Some applications to the study of metric fixed point theory are given.     

Signs of the Sine Illusion—Why We Need to Care

Graphical representations have to be true to the data they display. Computational tools ensure this on a technical level. But we also need to take “flaws” of the human perceptual system into account. The sine illusion provides an example where human perception leads to systematic bias in the assessment of the optical stimulus, with a particularly notable impact on perception of time-series data with a seasonal component. In this article, we discuss the reasons for the illusion and various strategies useful to break the illusion or reduce its strength. We demonstrate the presence of the illusion in real-world and theoretical situations. We also present data from a user study, which demonstrate the dramatic effect the sine illusion can have on conclusions drawn from displayed data.