客户/服务器产品

HP客户/服务器解决方案 HP公司于1982年推出UNIX版本操作系统,1986年推出RISC芯片,经过多年经验积累,不断完善,目前已宣布了第十个版本的UNIX操作系统HP-UX 10.0及第八代RISC芯片PA-8000。基于RISC/UNIX技术的HP9000服务器/工作站,与HP公司的PC机、X终端、中西文终端等构成了客户/服务器环境。同时HP公司还在全球实施传统大型主机替代计划,成功地协助数以千计的用户由封闭系统环境转向开放的客户/服务器环境,在保护用户以往投资的前提下,进一步增强应用环境的功能。     

台区客户信息智能梳理系统设计

为解决一些老城区电力用户归属不清的情况,设计一套信息智能梳理系统。该系统由客户信息检测终端和上位机管理平台两部分构成。检测终端采用低压电力线载波技术检测变压器辖区内集中器与采集器的连通性、确定电力客户与集中器的从属关系。上位机管理平台含台变参数设置、远程数据通信和检测数据存储查询等在线管理功能。测试结果表明,该系统的检测率达90%以上,成功梳理了测试中两个台区下的全部电力客户和集中器的从属关系。     

基于客户喜好的双向个性化推荐算法

为了解决现有推荐算法仅考虑同类产品间单向推荐所缺乏的灵活性,提升产品的销量及用户的购物体验,提出一种基于客户喜好的双向个性化推荐算法,不仅可以为客户精准推荐产品,还可以为商家推荐潜在客户.首先,基于产品购买网络中客户及其邻居的购买信息,扩展客户购买信息;其次设计客户产品喜好权重计算办法,分析客户的购买喜好,并在客户喜好的指导下为客户提供个性化的产品推荐;最后,基于商家提供的样本客户,挖掘与样本客户相似的客户构成社区,为商家提供潜在客户推荐以及精准客户维护.在真实数据集上的实验验证了算法的有效性.该算法从客户和商家两个维度出发实现了产品与客户的双向推荐,为个性化推荐领域的研究提供有益的帮助.     

WAP技术在供电企业营销客户服务中的应用

WAp技术应用于供电企业营销客户服务,可以创新企业营销客户服务手段,满足客户服务需求多样化的要求。本文简要介绍了WAP技术及如何应用该技术建设一套掌上客户服务系统,实现客户通过手机等手持终端随时随地进行业务办理及查询,也为进一步深化营销客户服务提供一个范例。     

电子商务客户流失的DBN预测模型研究

在电子商务迅速发展,企业快速抢占市场的背景下,客户成为企业竞争的核心因素。现有相关研究多致力于采用全数据输入模式解析客户流失现象,不同类型客户造成的差异性还有待进一步探讨。鉴于传统RFM模型不能精确解释电子商务客户流失原因,该研究将客户分为活跃与非活跃两个集群,提出一种优化的RFM理论模型与深度信念网络实证模型对电子商务客户流失进行预测。结果表明,不同类型客户流失因素的影响强度不同。对活跃用户而言,客户购买总金额是影响客户流失的主要因素;对非活跃用户而言,客户进入店铺的时间越长越可能留住客户。通过剖析非活跃用户不流失和活跃用户流失的原因,可帮助企业制定有效的客户管理策略,以最大程度地吸引潜在客户及保留现有客户,获取最多的市场利益。     

基于客户定制的产品配置

为了给客户提供一个直观和可视化的产品配置工具,研究了基于客户定制的产品配置模型,包括产品族功能模型、产品族装配模型以及产品配置知识的表达模型.利用该模型构建了一种面向客户基于Web的虚拟产品定制和展示环境,使得用户在该环境下可以提交需求目标,系统根据用户的需求进行配置,生成的产品三维实体模型可在浏览器中动态地观察和操作.     

应用因子分析和K-MEANS聚类的客户分群建模

为挖掘存量用户的潜在数据业务使用需求,研究客户细分成为各电信运营商进行差异化营销所必须解决的问题。利用聚类算法提出了一种解决电信短信业务客户分群的应用模型。首先基于因子分析为复杂参数变量下的数据挖掘有效地减少了冗余字段,提高了模型构建的质量和效率,然后通过无监督的K-MEANS分群算法完成分群。经验证,该短信分群模型具备明显的特征差异性。2009年某西部通信企业应用该模型在数据业务差异化营销中取得了明显的效益。     

阚孝全:倾听客户需求创新戴尔产品

记者:戴尔产品设计来自用户需求,家用产品是如何设计的? 阚孝全:用户将需求告诉戴尔,戴尔按需定制.戴尔从客户的直接反馈中获取信息,并针对客户反馈进行产品设计和改进.戴尔自己设计、并在自己的工厂中按需定制产品,从理念开始,到生产,再到产品的售后服务及支持,都是为了提高客户的体验,为客户提供更符合其需求的产品,得到了客户的广泛认可;同时,我们的产品设计在工业设计界也得到了很高认可.在过去一年中我们的家用产品获得了多个工业设计奖项,包括在德国和日本.     

基于并行分类算法的电力客户欠费预警

针对供电企业"先消费后付款"的经营模式可能造成用电客户因失信引发的欠费风险,需要在用电客户欠费行为发生之前实时快速地分析海量的用电用户的数据,给出潜在的欠费客户名单的问题,提出一种基于并行分类算法的电力客户欠费预警方法。首先,该方法使用基于Spark的随机森林(RF)分类算法对欠费用户进行建模;其次,根据用户以往历史用电行为和缴费记录使用时间序列进行预测得到其未来用电和缴费行为特征;最后,使用之前得到的模型对用户进行分类得到未来潜在高危险欠费用户。将该方法与并行化后的支持向量机(SVM)算法和在线序列极限学习机(OSELM)算法进行对比分析,实验结果表明,所提方法相对于对比算法在准确率上有较大提高,便于电费回收管理人员进行提前催缴,确保电费回收的及时性,有利于电力企业进行客户欠费风险管理。     

基于客户生命周期价值的客户分类与数据挖掘

本文在客户生命周期价值的基础上,运用贝叶斯、决策树等数据挖掘算法,挖掘出客户的现有价值、潜在价值和客户忠诚度,并以这三项指标为维度对客户进行分类,对不同类型的客户制定不同的营销策略.     

企业网站优化设计

建立一个成功的企业网站,可以全面塑造企业形象,帮助企业减少交易的代理、分销等中间环节,直接面对最终客户,降低销售成本,也可强化中小企业为国内外业界一流企业的品牌形象,有助于长期地留住访问者、培养潜在客户,从而增强中小企业在市场中的竞争能力。本文从企业网站的优化方面分析了怎样对企业网站进行优化设计。     

基于决策树算法的客服终端冗余数据迭代消除方法

为了提高客服终端数据可利用性,降低冗余数据干扰程度,挖掘潜在客户,制定销售策略,研究一种基于决策树算法的客服终端冗余数据迭代消除方法。采用数据仓库法抽取并集成客服终端数据,对字符类数据进行去停用词和中文分词预处理,对数值类数据进行缺失值填补和离散值删除预处理。构建ID3决策树,分类客服终端数据,计算同一类数据的类间相似度,构建冗余数据判断规则,检测客服终端冗余数据,联合消除器消除冗余数据。实验结果表明：所研究方法应用后,可以消除客服终端冗余数据,空间缩减比更接近冗余率。     

An anticipation model of potential customers’ purchasing behavior based on clustering analysis and association rules analysis

This paper proposes an anticipation model of potential customers’ purchasing behavior. This model is inferred from past purchasing behavior of loyal customers and the web server log files of loyal and potential customers by means of clustering analysis and association rules analysis. Clustering analysis collects key characteristics of loyal customers’ personal information; these are used to locate other potential customers. Association rules analysis extracts knowledge of loyal customers’ purchasing behavior, which is used to detect potential customers’ near-future interest in a star product. Despite using offline analysis to filter out potential customers based on loyal customers’ personal information and generate rules of loyal customers’ click streams based on loyal customers’ web log data, an online analysis which observes potential customers’ web logs and compares it with loyal customers’ click stream rules can more readily target potential customers who may be interested in the star products in the near future.     

客户可控制状态的银行客户账户管理系统

根据时间客户账户分为流动期和冻结期,在流动期内客户可进行账户查询、修改口令、取现、转账、冻结账户、退出管理全功能操作。在冻结期客户只能进行除取现和转账之外的半功能操作。如果账户处于流动期,客户可通过银行提供的客户账户管理终端设备随时将自己的账户转入冻结状态。如果客户希望自己的账户在t时处于活动状态,客户必须在t-T时之前通过银行客户服务终端将自己的账户解冻。     

Which is more important in Internet shopping,perceived price or trust?

Price and trust are considered to be two important factors that influence customer purchasing decisions in Internet shopping. This paper examines the relative influence they have on online purchasing decisions for both potential and repeat customers. The knowledge of their relative impacts and changes in their relative roles over customer transaction experience is useful in developing customized sales strategies to target different groups of customers. The results of this study revealed that perceived trust exerted a stronger effect than perceived price on purchase intentions for both potential and repeat customers of an online store. The results also revealed that perceived price exerted a stronger influence on purchase decisions of repeat customers as compared to that of potential customers. Perceived trust exerted a stronger influence on purchase decisions of potential customers as compared to that of repeat customers.     

Efficient metaheuristics to solve the intermodal terminal location problem

The objective of the intermodal terminal location problem is to determine which of a set of potential terminal locations to use and how to route the supply and demand of a set of customers (representing zones of supply and demand) through the network (by both uni- and intermodal transport) so as to minimize the total cost. Two different metaheuristic procedures are developed that both consist of two phases: a solution construction phase (either GRASP or attribute based hill climber) and a solution improvement phase based on local search. Innovative in this approach is the integration of a fast heuristic procedure to approximate the total cost given the set of open terminals. Both metaheuristics are compared to the results of an MIP solver. A thorough performance assessment uncovers that both metaheuristics generate close-to-optimal solutions in very short computing times. An argument in favor of the ABHC approach is that it is parameter-free and hence more transparent and likely to be accepted in a business or policy environment.     

Discovering patterns of online purchasing behaviour and a new‐product‐launch strategy

Spurred by rapid development of computers and Internet technology, online shopping is gradually overtaking in‐store shopping, because of advantages such as convenience, more choice of products or services etc. Online stores must devote a great deal of time and resources to locating and attracting new customers. Growing a customer base requires first understanding customers and then providing the products or services they need, thus encouraging customers to purchase more. This paper develops a system to analyse customers’ purchasing behaviour and track shifts in their interests. Customers’ purchasing behaviour is measured using proposed standard product loyalty status and standard brand loyalty status. Using these metrics, together with the preference map established for each customer, a marketing specialist can easily locate potential customers to target when a company launches a new product. The new‐product‐launch strategy proposed in this paper can be used to create a list of potential customers for a product being launched under a variety of conditions. A prototype system has been built to test the feasibility of the proposed new‐product‐launch strategy. The result shows almost 40% of potential customers respond to the recommendation positively.     

Adaptive Automated Teller Machines

Nowadays, Automated Teller Machines (ATMs) provide significant online support to bank customers. A limitation of ATM usage is that customers often have to wait in a queue, especially at ATMs installed at busy locations. Also, old people tend to consume more ATM usage time, possibly frustrating customers in the queue. In these situations, ATMs should “adapt” to the behavior of the customers to minimize the usage time. To this end, we apply data mining techniques to an ATM transaction dataset obtained from an international bank based in Kuwait. We pre-process this dataset, and convert it into a specific XML format to mine it through the ProM (process mining) tool. Our results reveal that customers withdraw money most frequently, followed by purchases (through an ATM card) and balance inquiry transactions. Customers re-do these transactions frequently, and also employ them one after the other. We acquire the distributions of the withdrawn amount, based on individual customers, the location (ATM terminal) and time of the withdrawl. Based on these results, we have proposed a set of five adaptive ATM interfaces, which show only frequent transactions and frequently-withdrawn amounts, display the current balance autonomously, and query explicitly for viewing purchase history, or for performing another withdrawl. An online survey on 216 ATM customers reveals that a majority of customers are willing to use these interfaces for minimizing their usage time. Our work has been approved by the banking authority of Pakistan, and we are currently implementing our interfaces for a Pakistani bank.     

Integrated intelligent techniques for remarshaling and berthing in maritime terminals

Maritime container terminals are facilities where cargo containers are transshipped between ships or between ships and land vehicles (trucks or trains). These terminals involve a large number of complex and combinatorial problems. Two important problems are the container stacking problem and the berth allocation problem. Both problems are generally managed and solved independently but there exist a relationship that must be taken into account to optimize the whole process. The terminal operator normally demands all containers bound for an incoming vessel to be ready in the terminal before its arrival. Similarly, customers (i.e., vessel owners) expect prompt berthing of their vessels upon arrival. This is particularly important for vessels from priority customers who may have been guaranteed berth-on-arrival service in their contract with the terminal operator. To this end, both problems must be interrelated.In this paper, a set of artificial intelligence based-techniques for solving both problems is presented. We develop a planning technique for solving the container stacking problem and a set of optimized allocation algorithms for solving the berth allocation problem independently. Finally we have developed an architecture to solve both problems in an integrated way. Thus, an algorithm for solving the berth allocation problem generates an optimized order of vessels to be served meanwhile our container stacking problem heuristics calculate the minimum number of reshuffles needed to allocate the containers in the appropriate place for the obtained ordering of vessels. Thus combined optimal solutions can be calculated and the terminal operator could decide which solution is more appropriate in each case. These techniques will minimize disruptions and facilitate planning in container terminals.