Abstract With the evolution of China's market economy, the securities market is increasingly anchoring a pivotal role in the nation's economic landscape. Consequently, stock trend forecasting has garnered heightened attention among scholars and practitioners. This research pioneers the use of multimodal information to predict stock market fluctuations. Based on our experimental results, LSTM + Transformer performs better in handling multimodal data for stock movement prediction tasks regarding accuracy, F1-score, precision, and recall. Additionally, we employed the Granger causality test and Impulse response test to investigate the causal relationships between sentiment and stock trends, as well as the interplay between COVID-related indicators and stock trajectories. We identified discernible causal links between sentiments, COVID indicators, and stock trends for select pharmaceutical stocks. Our findings can provide valuable guidance for investors and market regulators, especially within the pharmaceutical industry. Understanding investor sentiment and the impact of the pandemic on severity can assist in effective stock commentary management and improve investment strategies.

Abstract Recently, fake news detection on social media (SM) has attracted a lot of attention. With the emergence of fake news at a breakneck pace, the massive spread of fake news has had a serious impact in our society. The authenticity of the news is questionable and there exists a necessity for an automated tool for the detection. However, most fake news detection methods are mainly supervised, requiring huge amounts of annotated data, which is time-consuming, expensive, and almost impossible with vast new SM volume. To deal with this problem, in this paper, we propose a novel unsupervised fake news detection framework based on structural contrastive learning by combining the propagation structure of news and contrastive learning to achieve unsupervised training. To validate the influence of parameters and our method’s performance, we design experiment sets on public Twitter and Weibo datasets, which validate our approach outperforms current baseline ones and has proper robustness.

Abstract Malicious sellers frequently collaborate with spammers to fabricate reviews for promoting their products. These spammers act strategically in groups and have even formed black-and-gray industry chains. Researchers have proposed Frequent Item Mining-based, review burst-based, and graph-based schemes for spammer group detection. However, existing graph-based schemes often model reviewer relationships as a homogeneous network, failing to fully utilize the relationship semantics between reviewers or account for the burst characteristics of reviews, resulting in poor detection performance. Thus, this research proposes a cross-view contrastive learning-based spammer group detection algorithm for heterogeneous networks. To mine and embed the burst characteristics of reviews, we first filter out the target products and mine the active sessions of reviews about these products. We then construct a heterogeneous network featuring four node types and devise three unique meta-paths. Additionally, we utilize the cross-view contrastive learning method to learn the reviewer embeddings and apply DBSCAN to identify suspected groups for subsequent cleansing and ranking, ultimately determining potential spammer groups. Our experiments show the detection performance of the proposed scheme outperforms baseline ones.

This position article summarizes the panelists’ presentations and discussions at the panel “Fake News, Misinformation, and Privacy: How COVID-19 Pandemic Changed Our Society,” held at the 15th International Conference on Information Resources Management (Conf-IRM 2022) on October 18, 2022. The panel discussed their views on (1) how to stop the spreading of health misinformation; (2) how information sources affect online health information behavior; (3) how news literacy increases people's desire to seek out information by increasing their skepticism; and (4) how political beliefs, trust, and privacy concerns affect people's decisions during COVID-19. This article also discusses how blockchain and distributed ledger technologies can help tackle the fake news and misinformation problem.

Abstract It is not uncommon for malicious sellers to collude with fake reviewers (also called spammers) to write fake reviews for multiple products to either demote competitors or promote their products’ reputations, forming a gray industry chain. To detect spammer groups in a heterogeneous network with rich semantic information from both buyers and sellers, researchers have conducted extensive research using Frequent Item Mining-based and graph-based methods. However, these methods cannot detect spammer groups with cross-product attacks and do not jointly consider structural and attribute features, and structure-attribute correlation, resulting in poorer detection performance. Therefore, we propose a collaborative training-based spammer group detection algorithm by constructing a heterogeneous induced sub-network based on the target product set to detect cross-product attack spammer groups. To jointly consider all available features, we use the collaborative training method to learn the feature representations of nodes. In addition, we use the DBSCAN clustering method to generate candidate groups, exclude innocent ones, and rank them to obtain spammer groups. The experimental results on real-world datasets indicate that the overall detection performance of the proposed method is better than that of the baseline methods.

Content crowdsourcing, which refers to the mechanisms of individuals’ contribution to the common subject matters, followed by consolidation, is increasingly common.1 One of the most successful cont...

In recent years, machine learning has been used for data processing and analysis, providing insights to businesses and policymakers. Deep learning technology is promising to further revolutionize this processing leading to better and more accurate results. Current trends in information and communication technology are accelerating widespread use of web services in supporting a service-oriented architecture (SOA) consisting of services, their compositions, interactions, and management. Deep learning approaches can be applied to support the development of SOA-based solutions, leveraging the vast amount of data on web services currently available. On the other hand, SOA has mechanisms that can support the development of distributed, flexible, and reusable infrastructures for the use of deep learning. This paper presents a literature survey and discusses how SOA can be enabled by as well as facilitate the use of deep learning approaches in different types of environments for different levels of users.

In a business cloud environment, a reference business process model needs to be customized in order to meet the individualized requirements of each organization. Consequently, a reference process model is generally evolved to a couple of process variants, known as a process family. Currently, there exist some approaches and tools that can efficiently configure a reference process model. However, a key issue is how to manage co-evolution appropriately within a family of process models if the base process model of a process family is changed. Contemporary process management tools do not adequately support the management of such co-evolution. Each process variant in the process family has to be changed as a separate process model which often leads to redundancies and inefficiencies. In this article, we propose a novel approach for managing co-evolution of process families based on an aspect-oriented approach. Change options on base process model are abstracted and extracted as a pluggable component, which can be selectively reused for all members, and consequently, guides the co-evolution for the whole process family. In particular, the control-flow and data-flow relations between process extension and a member of process families can be built by leveraging process extensibility patterns. The correctness of our extension approach is proved based on graph theory. The whole approach in this article have been implemented as a working open-source prototype and tested against a real case study from the city logistic distribution domain as well as real data set from SAP reference models.

Ancient language manuscripts constitute a key part of the cultural heritage of mankind. As one of the most important languages, Chinese historical calligraphy work has contributed to not only the Chinese cultural heritage but also the world civilization at large, especially for Asia. To support deeper and more convenient appreciation of Chinese calligraphy works, based on our previous work on the probabilistic retrieval of historical Chinese calligraphic character manuscripts repositories, we propose a system framework of the multi-feature-based Chinese calligraphic character images probabilistic retrieval in the mobile cloud network environment, which is called the DPRC . To ensure retrieval efficiency, we further propose four enabling techniques: (1) DRL-based probability propagation, (2) optimal data placement scheme, (3) adaptive data robust transmission algorithm, and (4) index support filtering scheme. Comprehensive experiments are conducted to testify the effectiveness and efficiency of our proposed DPRC method.

Service-Oriented Computing (SOC) has recently gained attention both within industry and academia; however, its characteristics cannot be easily solved using existing distributed computing technologies. Composition and interaction issues have been the central concerns, because SOC applications are composed of heterogeneous and distributed processes. To tackle the complexity of inter-organizational service integration, the authors propose a methodology to decompose complex process requirements into different types of flows, such as control, data, exception, and security. The subset of each type of flow necessary for the interactions with each partner can be determined in each service. These subsets collectively constitute a process view, based on which interactions can be systematically designed and managed for system integration through service composition. The authors illustrate how the proposed SOC middleware, named FlowEngine, implements and manages these flows with contemporary Web services technologies. An experimental case study in an e-governmental environment further demonstrates how the methodology can facilitate the design of complex inter-organizational processes.

Workforce management is an important issue for human involved collaboration. When multiple urgent events simultaneously happen at different places with unexpected requirements, administrators should schedule workforce under the consideration of both system and user context, such as event requirements, user qualifications, etc. In this paper, we tackle this challenging problem of scheduling workforce for multiple urgent events. We study the Feasible Workforce Assignment Problem (WAP) that determines whether a system state satisfies the requirements of a given multiple-event scenario. Then, we present an efficient polynomial solution to solve it, with a case study to illustrate the effectiveness of our method.

In a general context, the sharing of intermediate service results among different processes is seldom feasible because parameters are often different and there may be transactional and side effects. However, in a streaming video multicast environment, a large number of users often request various similar processing on the same stream. Therefore, service sharing is feasible, with a large potential of savings in processing cost. In this paper, we study the problem of determining the service invocation orders for multiple service composition requests in a streaming video multicast with the aim of maximizing the service sharing. We first formally define the problem. After proving the problem is NP-complete, we develop an optimal algorithm for the base case of two requests. Then for the general case, we develop two heuristic algorithms, namely,aglobal greedy algorithm and a local greedy algorithm using the optimal algorithm for the base case as the building block. The global greedy algorithm is designed for a system where the existing service composition requests can be recomposed with the arrival of a new request. The local greedy algorithm can be used in a system where the existing service composition requests do not change their service composition solutions with the arrival of a new request. We prove that the global greedy algorithm is a 2-approximation algorithm in terms of maximizing service sharing. Simulation results show that the greedy algorithms can save more service costs compared with a naive algorithm, and are effective compared with the cost lower bound.

With the recent advances in Internet and mobile technologies and infrastructures, there are increasing demands for ubiquitous access to tourist information systems for service coordination and integration. However, disparate tourist information and service resources such as airlines, hotels, tour operators, etc., make it difficult for tourist to use them effectively when planning their trips and/or during their trips. Motivated by the emerging technologies of multi-agent information system (MAIS) and its ability to aid Internet and mobile users, together with semantic Web that can effectively organize information and service resources. In this paper, we propose a virtual travel agent system (VTAS), which is built upon these technologies. In this paper, we formulate a scalable, flexible, and intelligent MAIS architecture for VTAS with agent clusters based on a case study of a large service-oriented travel agency. Agent clusters may comprise several types of agents to achieve the goals of the major processes of a tourist's trip. We show how agents can make use of ontology from the semantic web help tourists better plan, understand, and specify their requirements. We further illustrate how this can be successfully implemented with Web service technologies to integrate disparate Internet tourist resources.

Efficient and effective management is a key to business success. In particular, process management technologies can help smoothen and enhance the production. In this paper, we propose a sophisticated alert management system (AMS) for workflow management in particular for concrete batching plant. For concrete batching plant, there are challenges in monitoring schedules and handling their changes. An AMS can help monitor the whole production process and keep track of any exceptions by sending alerts and receiving responses in order to assist in resources planning and production scheduling of relevant stakeholders. We develop a model for specifying alerts and outlining the mechanism of the AMS. The applicability of the AMS for workflow integration, data integration, and exception handling is also examined by studying the stakeholders ' requirements.

Enterprises value monitoring as it provides dependable e-services, whether it is an interactive Web site or programmatic Web service. However, this task becomes non-trivial when enterprises begin to require support from thousands of servers across geographical areas. How can the communications between a monitoring systems and remote servers be minimized? Could the task be achieved easily based on a readily available technology such as SNMP? How can we monitor thousands of servers powered by, say, Tomcat, which lacks SNMP support? How may a poorly responsive site be identified prior to being reported as a failure by SNMP? In this paper, we propose a unified e-monitoring system that enables system administrators to remotely monitor the health of distributed e-services in both the form of Web site and Web services. We further discuss our implementation experience based on a pragmatic prototype.

With the increase in personal wealth and organization sizes, there is also an increase in their assets. So, there is a great demand of professionals to manage these assets and coordinate investment activities in order to maintain the growth. Wealth management services are now widely offered by banks, trusts companies, and brokerages. As the financial market becomes well-developed worldwide, the variety of financial products also increases: equities, mutual funds, bonds, securities, foreign currencies, and derivatives (like options, futures, forwards, and swaps). As a wealth management system (WMS) plays the role of an order placement hub, it becomes more and more complicated during each enhancement to support order placement of additional kinds of financial products. This is because a WMS requires different channels to communicate with different instrument markets. For an international investment company, the problem comes more complicated because the order placement processes are heterogeneous in different countries and locations. In fact, trading systems for different instrument markets of different countries and even different cities are different. Workflows are also hard to coincide with different sites. Therefore, we propose the use of Web services to implement the workflow of order placement process

Effective and efficient process management is of paramount importance in today's businesses. This is also indispensable for the maintenance of public road system. Since the maintenance work involves lots of humans and critical conditions, the complex communication among government departments often delay progress of work and exceed the scheduled completion date. In order to shorten the time of communication among departments and facilitate the workflow of different maintenance stages, we develop a conceptual model of road maintenance management system (RMMS). The RMMS makes use of alert mechanism and Web services for B2B interactions for handling urgent requests of road maintenance work. By using Web services, the RMMS integrates the internal systems of various government departments and major service providers. Based on the information provided by the involved parties, the RMMS analyzes and handles urgent requirements automatically and therefore could maintain the timeliness and accuracy of public road maintenance services

Nowadays stocks are traded electronically instead of manually with an open outcry approach. As a result, business activities of investment banking organizations rely heavily on the availability of their trading systems. Any system failure will directly affect their business and in turn damage their reputation. Due to the complexity of the business, trading of stock requires services provided by many systems even within the same company. Any failure of a single system may stop the business. However, the monitoring of many systems simultaneously is not an easy task. This paper proposes a Web service approach to monitor all the systems related to stock trading within an investment banking organization. We develop a model for specifying how to detect potential system problems quickly, how to escalate the issues to relevant parities on time with an alert mechanism, and how to manage system outages properly

Recent advances in mobile technologies and infrastructures have led to increasing demands for ubiquitous access to enterprise services from mobile handheld devices, such as mobile phones and PDAs. The context in which such a service is used becomes an integral part of the associated enterprise application. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information. Instead of redesigning or adapting existing enterprise services in an ad-hoc manner, we introduce a methodology for the elicitation of context-aware adaptation requirements and the matching of context-awareness features to the target context by capability matching. For the implementation of these adaptations, we propose the use of three tiers of views: user interface views, data views, and process views. This approach centers on a novel notion of process views to service adaptation according to their context. We demonstrate our methodology by extending an enterprise appointment service into a ubiquitous one with context support

Persistent conversation has emerged and become the basis of many Web communities nowadays. It is also widely used in e-commerce and extended enterprises. The registration procedures for the users of most Web communities are unreliable and can be easily compromised. In this paper, we propose an anonymous and secure conversation protocol based on a concept of alias certificate with analysis to show that our scheme satisfies such requirements

With the recent advances in mobile technologies and infrastructures, there are increasing demands for ubiquitous access to tourist information systems for service coordination and integration. However, disparate tourist information and service resources make it particularly difficult for mobile tourists to use them effectively during their trips. Neither can current tourist portals assist tourists proactively or adequately to overcome this problem. Motivated by the emerging technologies of multi-agent information systems (MAIS) that can effectively assist mobile users together with Semantic Web that can effectively organize information and service resources, we propose a ubiquitous tourist assistance system (UTAS) be built upon these technologies. In this paper, we formulate a scalable, flexible, and intelligent MAIS infrastructure for a proactive UTAS with agent clusters based on a case study of a large service-oriented travel agency. Each agent cluster comprises several types of agents to achieve the goals of the major processes of a tourist's trip. We show how agents can make use of ontology from the Semantic Web to plan better as well as help tourists better understand and specify their requirements and preferences. We discuss and evaluate our approach from different stakeholders' perspective.

In the current service-oriented economy, professional workforce and service personnel have to make not only reasonable but also personalized recommendations in response to individual customer's query. This affects not only the likelihood that the customer takes the recommendations as a short-term benefit but also the service providers' reputation in a long run. However, as different customers have different risk attitudes, they have different trade-off between the service providers' reputation and the recommendations' utilities. Therefore, the classical decision model considering only the utility and success rate is inadequate. We reconsider the problem of making recommendations from multiple perspectives, including reputation and risk attitude. We explain how this model can facilitate service providers to make effective decisions at strategic, tactical, and operations level regarding service recommendations.

New technologies have introduced new ways in business transactions where online contracting is complementing and even substituting traditional paper-based transactions. One of the major recent innovations of online contracting is the use of intelligent agents to make contracts among users and businesses around the globe. Despite recent legislations on electronic contracting, there are no legislations governing automatic agent transactions except one preliminary attempt in the USA. We identify the key problem rooted at the authorization management in agent delegation as well as the proper legal identity of agents. Therefore, we advocate solutions that consider both legal and technical aspects. Based on current legal and business practices, we develop a conceptual model for agent authorization and identity management We propose an Agent Authorization Platform (AAP) for the enforcement of agent authorization during contract establishment as well as the maintenance of the legal identity of agents. The AAP also supports alerts and acknowledgment to further enforce the user's manifestation of assent to the contract terms. We also detail a required security scheme for the AAP based on Public Key Infrastructure (PKI) technologies to demonstrate the feasibility of our approach.

With the invention of new interaction devices and the requirements for ubiquitous access to application systems, user's interactions have moved beyond the desktop and evolved into a trend of ongoing development. The context in which the application is being used becomes an integral part of the activity carried out with the system. The inclusion of context-awareness provides convenience and efficiency to users for their ubiquitous access. Traditional human-computer interface (HCI) theories are now inadequate for developing these context-aware applications, as we believe that the notion of context should be extended to different categories: computing contexts, user contexts, and physical contexts for ubiquitous computing. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information. In this paper, we introduce a methodology for the elicitation of context-aware requirements and the matching of context-awareness features to the target context by capability matching. Based on this model, we analyze the design issues of some common ubiquitous access situations and show how to fit them systematically into a context-aware application by considering the requirements of a ubiquitous tourist application. Copyright 2005 ACM.

With the recent adoption of marketing activities outsourcing, there have been increasing demands and concerns for privacy control. The traditional approach of a bulk transmission of the customers' information to a marketing company cannot meet such demands, especially in the finance and healthcare businesses. Therefore, we propose a layered architecture and a development methodology for end-to-end privacy control over the export of each individual customer's records through a Web services platform, according to the corresponding enterprise's privacy control policies. A Web services system, with up-dated security and privacy facilities, can provide a suitable interoperation platform for required application-to-application interactions over the Internet. We further develop a conceptual model and an interaction protocol to send only the required part of a customer's records at a time. We illustrate our approach for end-to-end privacy control with a tele-marketing case study and show how the software of the outsourced call center can be integrated effectively with the Web services of a bank to protect privacy. Copyright 2005 ACM.

Despite the recent uprising of the Web Services technology for programmatic interfaces of business-to-business (B2B) E-commerce services (e-services) over the Internet, most existing sites can only support human interactions with Hypertext Markup Language (HTML) through web browsers. Automating third-party client access into Web Services generally requires developing sophisticated programs to simulate human access by handling HTML pages. However, these HTML interfaces vary across web sites, and are often subject to changes. Client maintenance is therefore tedious and expensive. Even for the site owner, it may still require much effort in redeveloping the underlying presentation and application logics. This motivates our study for the requirement and the formulation of a conceptual model for such automation. Based on the requirement, we develop a novel approach to automating dialogs with web-based services (particularly for cross-organizational processes), using a high-level script language, called WebXcript language. The language provides features for HTML forms-based dialogues and eXtended Markup Language (XML) messaging. The XML syntax of WebXcript further enables convenient user authoring and easy engine development with extensively available XML tools. It supports expected responses and exception handling. We further propose a wrapper architecture based on WebXcript to integrate legacy sites into Web Services, where Web Service Definition Language (WSDL) interfaces are generated from high-level mappings from database or WebXcript parameter definitions. We demonstrate the applicability of our approach with examples in integrating distributed information, online ordering, and XML messaging, together with discussions on our experiences and the advantages of our approach.

Recent advances in mobile technologies have greatly extended traditional communication technologies to mobile devices. At the same time, healthcare environments are by nature "mobile" where doctors and nurses do not have fixed workspaces. Irregular and exceptional events are generated in daily hospital routines, such as operations rescheduling, laboratory/examination results, and adverse drug events. These events may create requests that should be delivered to the appropriate person at the appropriate time. Those requests that are classified as urgent are referred to as alerts. Efficient routing and monitoring of alerts are keys to quality and cost-effective healthcare services. Presently, these are generally handled in an ad hoc manner. In this paper, we propose the use of a healthcare alert management system to handle these alert messages systematically. We develop a model for specifying alerts that are associated with medical tasks and a set of parameters for their routing. We design an alert monitor that matches medical staff and their mobile devices to receive alerts, based on the requirements of these alerts. We also propose a mechanism to handle and reroute, if necessary, an alert message when it has not been acknowledged within a specific deadline.

Despite recent uprising of the Web services technology for programmed interfaces of business-to-business (B2B) e-commerce services (e-services) over the Internet, most sites (e.g., online purchases) can only support Hypertext Markup Language (HTML) for human interactions through Web browsers. Automating client access to these services generally requires developing sophisticated programs to simulate human access by handling HTML pages and forms. However, these HTML interfaces vary across Web sites, and are often subjected to changes. Client maintenance is therefore tedious and expensive. This paper presents a novel approach to automate dialogs with Web-based services, using a high-level script language, called WebXcript. WebXcript provides features for HTML forms based dialogues and XML messaging. The XML syntax of WebXcript further enables convenient user authoring and easy engine development with extensively available XML tools. It supports expected responses and exception handling. We further propose a wrapper architecture to integrate heterogeneous Web services based on WebXcript. We demonstrate the applicability of our approach with examples in integrating distributed information, online ordering, and XML messaging.

With recent advances in mobile technologies and infrastructures, there are increasing demands for ubiquitous access to networked services. These services, generally known as m-services, extend supports from Web browsers on personal computers to handheld devices, such as mobile phones and PDAs. However, in general, the capabilities and bandwidth of these devices are significantly inferior to desktop computers over wired connections, which have been assumed by most Internet services. Instead of redesigning or adapting m-services in an ad-hoc manner for multiple platforms available in handheld devices, we propose a methodology for such adaptation based on three tiers: user interface views, data views, and process views. These views provide customization and help balance security and trust. User interface views provide alternative presentations of inputs and outputs. Data views summarize data over limited bandwidth and map heterogeneous data sources. In addition, we introduce a novel approach of applying process views to m-service adaptation, where mobile users may execute a more concise version or modified procedures of the original process. The process view also serves as the key mechanism for integrating user interface views and data views. In addition, we present a formal model on view consistency and integrity in our methodology. We demonstrate the feasibility of our methodology by extending a service negotiation subsystem into an m-service with multi-platform support.

E-services refer to services provided via the Internet. To provide value-added and composite e-services, we need an information system that can coordinate API-based, interactive web-based and human agents, internal and external to an organization. We present an environment to model and enact composite e-services as workflows, by extending our ADOME-WFMS (Advanced Object Modeling Environment-Workflow Management System) to E-ADOME, which supports composing new e-services and effective management of agents for enacting e-service.

Workflow is automation of a business process. A Workflow Management Systems (WFMS) is a system that assists in defining, managing and executing workflows. To support flexible enactment and adapive features, such as on-line workflow evolutionand exception handling, a WFMS requires advanced modeling functionality. As workflow evolution requires the modification of workflow definitions or adding ECA rules to the system during work in progress, an advanced schema evolution capability is required at run-time. It should be noted that the resolutions based on schema evolution are general-purpose ones, which can help reduce the occurrence of additional exceptions. As such, we have developed ADOME-WFMS based on Advanced Object Modeling Evnironment (ADMOE [4] - - an active OODBMS with role and synamic schema suppport), with a novel exception centric apporach. The contribution and objectives of our research with respect to workflow evolution are as follows.

Exception handling in workflow management systems (WFMSs) is a very important problem since it is not possible to specify all possible outcomes and alternatives. On the other hand, cooperative support for user-driven computer supported resolution of unexpected exceptions and workflow evolution at run-time is vital for an adaptive WFMS. We have been developing ADOME-WFMS as a comprehensive framework in which the problem of workflow exception handling can be adequately addressed. We present an adaptive exception manager and its Web-based interface for ADOME-WFMS with procedures for supporting the following: effective management of problem solving agents, cooperative exception handling, user-driven computer supported resolution of unexpected exceptions, and workflow evolution.

Summary form only given. The paper discusses exception handling in ADOME workflow management system (WMS). ADOME (Advanced Object Modeling Environment) is an active OODBMS extended with role facilities, built by integrating ITASCA (OODB) and CLIPS (inference engine). It provides a good supporting environment for the dynamic features required for a workflow management system, especially for online exception handling. In ADOME-WFMS, exception handlers can be procedural (extra branches of existing activity decomposition for exception handling) or declarative (in the form of ECA rules that can be specified within the scope of different activity and sub-activity levels).