Kontextbasierte Kooperation für mobile Geschäftsanwendungen

Realistic requirements of mobile business applications often exceed the capabilities of their respective local environments. In order to overcome such restrictions of specific mobile devices, services, and resources, this contribution introduces the concept of context-based cooperation. It is based on mobile processes which enable applications to cross boundaries of individual systems and thereby allow combining both mobile and stationary resources in order to realize highly dynamic individual applications. This contribution presents an approach for realizing context-based cooperation built upon on a respective context management infrastructure and execution environment. It also identifies specific requirements and proposes related enhancements for mobile business applications.     

Processing online analytics with classification and association rule mining

Business performance measurements, decision support systems (DSS) and online analytical processing (OLAP) have a common goal i.e., to assist decision-makers during the decision-making process. Integrating DSS and OLAP into existing business performance measurements hopes to improve the accuracy of analysis and provide in-depth, multi-angle view of data. This paper describes a decision support system containing our methodology, Weighted and Layered workflow evaluation (WaLwFA), extended to incorporate business intelligence using C4.5 and association rule algorithms. C4.5 produces more comprehensible decision trees by showing only important attributes. Furthermore, C4.5 can be transformed into IF-THEN rules. However, association rules are preferred as data can be described in rules of multiple granularities. Sorting rules based on rules’ complexities permits OLAP to navigate through layers of complexities to extract rules of relevant sizes and to view data from multidimensional perspectives in each layer. Experimental results on an airline domain are presented.     

A weight and a meta-analysis on mobile banking acceptance research

Following the globalization of business and systems, there is a pressing need to understand the main factors affecting mobile banking user acceptance. The increasing number of mobile banking studies and articles published in the last years, as well as conferences and workshops, has made the research process on this important subject more complex and time-consuming. Therefore, it is necessary to synthesize findings from existing research, seeking an update of the current state-of-the-art knowledge. A combination of weight and meta-analysis was chosen, in order to identify the frequency and relevance of the most used constructs and their most important relationships. A total of 57 articles were found in the literature, having the necessary quantitative statistical data to be considered. The best predictors of the intention to use the mobile banking services identified, simultaneously significant in the weight and in the meta-analysis, are: (i) attitude, (ii) initial trust, (iii) perceived risk, and (iv) performance expectancy. In terms of use of mobile banking, considering the same assumptions, the best predictors are: (i) intention, and (ii) performance expectancy. Facilitating conditions on attitude, task technology fit on performance expectancy, and performance expectancy on initial trust have the potential to be added to the list of the most important predictors, but they still need additional research. A theoretical model based on our results is presented, providing a means to support future mobile banking acceptance studies.     

Boosting social collaborations based on contextual synchronization: An empirical study

Supporting context-based collaboration among online users is an important issue to computer-mediated collaboration to fulfill specified tasks. However, several problems make it difficult to be aware of the context. The context of the user task can be (i) dynamic (i.e., changing over time), and (ii) mixed with multiple sub-contexts together. We propose a novel ontology-based platform to overcome these problems. It finds the most relevant users from a given social network, taking into account two types of context (i.e., personal and group contexts) and matching them. By measuring similarities between the personal contexts, we can dynamically organize a number of communities, so that users can be contextually synchronized. Individual users can be involved in complex collaborations related to multiple semantics. This paper demonstrates and discusses how the proposed context synchronization process is able to boost social collaborations. We show the experimental results collected from a collaborative information searching system. The main empirical issues in this work are (i) setting thresholds, (ii) searching performance, and (iii) scalability testing.     

Using context for online customer re-identification

The task of re-identification consists of linking records for individuals with no identifying information to records with identifying information (i.e., name or social security number) in order to identify individuals within the anonymous data. This task is important for business since firms want to precisely identify consumers for several reasons, such as targeting advertisements to them or labeling them as fraudulent users. For these reasons, companies strive to improve their re-identification techniques. In addition, the re-identification task is relevant from a research prospective, and many algorithms and techniques have been proposed to improve existing re-identification models. However, no previous research has studied whether the use of contextual variables can improve re-identification performance. Context can be defined as the circumstances under which transactions take place. To date, contextual information (i.e., the time of day when or the location where digital data was created) has been used successfully in other modeling tasks such as in the recommender system domain, where its ability to improve the accuracy of lists of items suggested to website users has been demonstrated. Including contextual information in a re-identification model is not a trivial task for several reasons. In this paper, we discuss the main issues regarding the use of context for the re-identification task, namely, when incorporating context is expected to help re-identification and when it is expected to hurt. We propose contextual re-identification models and a framework for deciding when to use these and determining the best performing contextual method for the re-identification task. We test our contextual models using three different case studies. Our findings have a significant impact on expert and intelligent systems since they provide the first evidence of the possibility of including contextual variables for improving the results of the re-identification process. The results also have a relevant impact for businesses since they can help managers decide when and how to include a contextual variable into the re-identification task and contextualize subsequent actions after the re-identification task.     

一种上下文移动用户偏好自适应学习方法

针对移动网络对个性化移动网络服务系统的性能提出了更高的要求,但现有研究难以自适应地修改上下文移动用户偏好以为移动用户提供实时、准确的个性化移动网络服务的问题,提出了一种上下文移动用户偏好自适应学习方法,在保证精确度的基础上缩短了学习的响应时间.首先,通过分析移动用户行为日志来判断移动用户行为是否受上下文影响,并在此基础上判断移动用户行为是否发生变化.然后,根据判断结果对上下文移动用户偏好进行修正.在对发生变化的上下文移动用户偏好进行学习时,将上下文引入到最小二乘支持向量机中,进一步提出了基于上下文最小二乘支持向量机(C-LSSVM)的上下文移动用户偏好学习方法.最后,实验结果表明,当综合考虑精确度和响应时间两方面因素时,所提出的方法优于其他学习方法,并且可应用于个性化移动网络服务系统中.     

Modelling mobile app requirements for semantic traceability

The paper presents a modelling method aimed to support the definition and elicitation of requirements for mobile apps through an approach that enables semantic traceability for the requirements representation. Business process-centricity is employed in order to capture requirements in a knowledge structure that retains procedural knowledge from stakeholders and can be traversed by semantic queries in order to trace domain-specific contextual information for the modelled requirements. Consequently, instead of having requirements represented as natural language items that are documented by diagrammatic models, the communication channels are switched: semantically interlinked conceptual models become the requirements representation, while free text can be used for requirements annotations/metadata. Thus, the method establishes a knowledge externalization channel between business stakeholders and app developers, also tackling the Twin Peaks bridging challenge (between requirements and early designs). The method is presented using its modelling procedure as a guiding thread, with each step illustrated by case-based samples of the modelling language and auxiliary functionality. The design work is encompassed by an existing metamodelling framework and introduces a taxonomy for modelling relations, since the metamodel is the key enabler for the goal of semantic traceability. The research was driven by the ComVantage EU research project, concerned with mobile app support for collaborative business process execution. Therefore, the project provides context for the illustrating examples; however, generalization possibilities beyond the project scope will also be discussed, with respect to both motivation and outcome.     

Applying business context to calculate subsets of business document standards

Business documents directly exchanged between applications usually follow a certain business document standard. No matter whether these standards are traditional EDI standards or XML-based, they are very generic including all elements that may be of need to any company in this world. Before being used in a partnership, a subset of these elements has to be defined based on the business context (geopolitical region, industry, etc.). Usually the definition of these subsets—called Message Implementation Guidelines—starts from scratch, and, thus, is very time-consuming. In this paper we present an approach to explicitly assign context to the definition of Message Implementation Guidelines. This contextual information is also used to calculate a subset for to-be-developed Message Implementation Guidelines based on existing ones. The corresponding approach is supported by a prototype implementation.     

A method to infer the need to update situations in business process adaptation

Contextual knowledge is an essential resource for adapting business processes in order to keep them aligned with its goals. A context-based adaptation environment should learn from the dynamism of the context as well as the decisions made, and continuously identify new unforeseen situations. Data mining is a possibility to maintain the analysis of the processes updated. This paper presents a method that infers the need to learn new situations that influence a business process execution. The method is based on the results of the Apriori algorithm application. Case studies were conducted to evaluate the proposal. We observed evidences of context changes over time and the potential to learn with this dynamics through the method proposed.     

An effective database formation for decision support systems

Managers' tasks have two aspects: to monitor (control) business activities and to plan the future based upon the monitored results. Thus a decision Support System (DSS) must have two kinds of databases appropriate for its needs.A management database, i.e., one for monitoring activities, is constructed mainly from the existing operational databases. A data cube should be employed for the logical data structure of the management database so that managers can share it and access it in multiple ways.Planning databases, i.e., those for planning activities, are constructed mostly from the management database. A table form should be employed for its logical data structure so that managers will find it easy to use.The management and planning databases should be connected through DSS's system architecture [1]. This makes the operational data (indicating business activities) directly and immediately available for management decision making.We have previously presented the DSS architecture. This paper discusses the management and planning databases from the viewpoint of it.     

基于Android的QR Code名片系统研究

名片是一种常用的社交工具。在接到别人的纸质名片后,将名片上的信息逐条存入手机通信录中比较繁琐,不及时存储,纸质名片又容易丢失。为了解决这个问题,在Android开源手机平台的基础上,设计并实现QR Code名片系统,让用户可以方便及时地将纸质QRCode名片上的信息存储到入手机通信录中,方便实用。     

What Software Security Means to Business

Software security: we know we want it, we make choices and tradeoffs that have implications for it, yet, in a general sense, it has escaped true definition and defied measurement. Definition and measurement though are sequential, meaning that something must be defined to make any comparisons against it. In a technical sense, many have positioned software security as protecting the confidentiality, integrity and availability of data, resources and sometimes the application itself. This „definition” tries to capture security broadly but in practice the importance of these things — and the value that defending them has to an organization — varies wildly. More important than defining what security is, we need to capture what it means in context, and what it costs. The only definition that really matters to the enterprise then is one that deals with the contextual nature of security, risk, and pain. This paper is an attempt to explore what software security means to enterprises. Its purpose is to lay the foundation for software security metrics that are truly actionable by the business community to help drive security decisions for the software they buy, build, and outsource. The thoughts, ideas, insights and proposals here come from the members of the Application Security Industry Consortium (AppSIC)0, a group of software security executives, researchers, analysts and practitioners from the vendor, enterprise consumer, academic, and analyst communities. Our intention in writing it is to spur debate on the topic, and, through the input of the community, create a foundation upon which to build software security metrics that are meaningful to business.     

基于Android的QRCode名片系统研究

名片是一种常用的社交工具。在接到别人的纸质名片后,将名片上的信息逐条存入手机通信录中比较繁琐,不及时存储,纸质名片又容易丢失。为了解决这个问题,在Android开源手机平台的基础上,设计并实现QRCode名片系统,让用户可以方便及时地将纸质QRCode名片上的信息存储到入手机通信录中。方便实用。     

Literature review of reuse in business process modeling

Business process models play an important role in the analysis and improvement of the performance of an enterprise. Evidently, the quality of a business process model has a direct effect on the business performance. This evidence has motivated both the academic and industrial communities to look for suitable methods for creating good quality business process models. In particular, there is a wide agreement that reuse can accelerate the design process and produce high quality solutions by adopting best practices and agreed-up-on solutions. However, faced with various types of reusable artifacts, business process designers need a set of criteria to determine which type would suit best their needs and design context. To assist designers in their choice, we first present a set of criteria influencing the design phase in terms of effort required and the quality of the resulting model. Secondly, we use this set of criteria to present a state of the art on the most significant reusable design artifacts.     

The conceptual model of context for mobile commerce applications

Mobile commerce applications adhering to anytime and anywhere paradigm, required to be flexible. They should be able to adapt their interface, services and content towards a certain context. Several proposals for definition of context have been already proposed originating from various areas related to mobile commerce. However, an integrated, formal and methodological approach for the determination and representation of context, adjusted to special characteristics of mobile commerce applications, has not been insofar presented. This is the challenge we address in this paper, through a conceptual model that includes: i) a clear and formal definition of context, ii) the depiction of its specific characteristics as metadata, iii) a methodology for its determination and iv) the presentation of an extension of class diagrams of UML for its representation, all of them tailored to the special nature of mobile commerce applications.     

Introducing decision-aware business processes

Business processes are designed to smoothly operate under multiple contexts (or business situations). Each context technically implies taking a different course of action. Be that as it may, going for the most appropriate action is still left up to the business process participant without any kind of assistance. Such a situation demonstrates that there is a lack of a context-aware decision-making feature. This paper addresses the issue of enabling a context-aware decision-making within the frame of business processes. We combine the concepts of business process, context-awareness and decision-making to introduce a new concept of Decision-Aware Business Processes in which decision partitions are the cornerstones. A decision partition reacts to the collected contextual parameters by selecting or recommending the most appropriate decision(s). In fact, the focus of this research is to introduce a new formalism for designing these partitions by means of patterns. Throughout our approach, each proposed pattern leads to building decision partitions in a straight-forward fashion. An overall example is proposed to illustrate our approach. It is inspired from the banking industry and introduces a decision-aware business process that handles loan applications. To sum up, whether seasoned, novice or in-between, business process participants will be able to save time in taking action(s). Moreover, the workflow becomes no longer stagnant across the business process. Instead, it dynamically adapts itself to each new set of business requirements imposed by the collected contextual input(s).     

Bridging Real World Semantics to Model World Semantics for Taxonomy Based Knowledge Representation System

As a mean to map ontology concepts, a similarity technique is employed. Especially a context dependent concept mapping is tackled, which needs contextual information from knowledge taxonomy. Context-based semantic similarity differs from the real world similarity in that it requires contextual information to calculate similarity. The notion of semantic coupling is introduced to derive similarity for a taxonomy-based system. The semantic coupling shows the degree of semantic cohesiveness for a group of concepts toward a given context. In order to calculate the semantic coupling effectively, the edge counting method is revisited for measuring basic semantic similarity by considering the weighting attributes from where they affect an edge's strength. The attributes of scaling depth effect, semantic relation type, and virtual connection for the edge counting are considered. Furthermore, how the proposed edge counting method could be well adapted for calculating context-based similarity is showed. Thorough experimental results are provided for both edge counting and context-based similarity. The results of proposed edge counting were encouraging compared with other combined approaches, and the context-based similarity also showed understandable results. The novel contributions of this paper come from two aspects. First, the similarity is increased to the viable level for edge counting. Second, a mechanism is provided to derive a context-based similarity in taxonomy-based system, which has emerged as a hot issue in the literature such as Semantic Web, MDR, and other ontology-mapping environments.