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Changes in workflow relevant data of business processes at run-time can hinder their completion or impact their profitability as they have been instantiated under different circumstances. The purpose of this paper is to propose a context engine to enhance a business process management (BPM) system’s context-awareness. The generic architecture provides the flexibility to configure processes during initialization as well as to adapt running instances at decision gates or during execution due to significant context change.

The paper discusses context-awareness as the conceptual background. The technological capabilities of business rules and complex event processing (CEP) are outlined in an architecture design. A reference process is proposed and discussed in an exemplary application.

The results provide an improvement over the current situation of static variable instantiation of business processes with local information. The proposed architecture extends the well-known combination of business rules and BPM systems with a context engine based on CEP.

The resulting architecture for a BPM system using a context engine is generic in nature and, hence, requires to be contextualized for situated implementations. Implementation success is dependent on the availability of context information and process compensation options.

Practitioners receive advice on a reference architecture and technology choices for implementing systems, which can provide and monitor context information for business processes as well as intervene and adapt the execution.

Currently, there is no multi-purpose non-proprietary context engine based on CEP or any other technology available for BPM, which facilitates the adaptation of processes at run-time due to changes in context variables. This paper will stimulate a debate between research and practice on suitable design and technology.

Context‐aware mobile computing extends the horizons of the conventional computing model to a ubiquitous computing environment that serves users at anytime, anywhere. To achieve this, mobile applications need to adapt their behaviors to the changing context. The purpose of this paper is to present a generalized adaptive middleware infrastructure for context‐aware computing.

Owing to the vague nature of context and uncertainty in context aggregation for making adaptation decisions, the paper proposes a fuzzy‐based service adaptation model (FSAM) to improve the generality and effectiveness of service adaptation using fuzzy theory.

By the means of fuzzification of the context and measuring the fitness degree between the current context and the predefined optimal context, FSAM selects the most suitable policy to adopt for the most appropriate service. The paper evaluates the middleware together with the FSAM inference engine by using a Campus Assistant application.

The paper is of value in presenting a generalized adaptive middleware infrastructure for context‐aware computing and also comparing the performance of the fuzzy‐based solution with a conventional threshold‐based approach for context‐aware adaptation.

The purpose of this paper is to propose an intelligent service recommendation model. The paper formulates the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rule based reasoning.

The authors formulate the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rule based reasoning. Bayesian Network is used to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the rules for adopting the policies of implementing a service, fitness degree computation and service recommendation. In addition to this the paper proposes maximum to minimum priority based context attributes matching algorithm for rule selection based on fitness degree of rules. The context aware mobile is tested for library and class room scenario to exemplify the proposed service recommendation engine and demonstrate its effectiveness.

First, it was found that there was reduction in application searching time in different contexts. For example, if user enters into the library, the proposed mobile will be adapted to the library situation automatically by configuring its desktop and internal settings to facilitate the library services like book search, web link, silent mode and friends search. Second, the design of the recommendation engine, utilizing contextual parameters like Location (class room, college campus, house, etc.) Personal (age, name), Temporal (time, date), Physical (fall, normal), and schedule agendas, was found to be of importance.

Exploitation of hybrid fuzzy system, Bayesian Networks and the utility theory (usage history and context history) for modeling and implementation.

The purpose of this paper is to provide useful insights underlying the popularity of search engine technologies within a social media-intensive environment.

The degree of social interaction for social media platforms that integrate search engine technologies as part of the homepage and related experience is very mixed on part of its users. Through Barnard’ theory of authority acceptance, social media and its popularity may be examined by the ability of its users to create effective messages that can be broadcasted to many, yet controlled by individual. The hypotheses tested the interaction of social media and search engine with gender and technological ease-of-use factors.

The statistical evidence suggested that significant technological and ease-of-use aspects of search engines are not meaningful, based on gender alone. Males may slightly be prone to take advantage of such technologies, but their search and use patterns are not much varied from their female counterparts. Social media, generally more fully captured authority in individual search patterns, and a number of interactions among gender status, search engine characteristics, and social media were found to be significant and profound. The testing of these hypotheses directly reflect the complexities of unique needs among users of search engines within a social media environment.

Search engine technologies with a social media context has allowed for the development of a modern, user-driven internet experience that has been powered by users’ imagination and is designed to at least partially satisfy users’ need for self-directed engagement. Organizations are well advised to provide a mindful, less controlled, and more interactive presence of potential users, especially through an increasingly mobile presence.

Individuals as well as organizations are rapidly discovering that it is becoming easier to share and distribute their content, especially for more creative and innovative content, among all of its users. As businesses continue to focus on the quality of one’s own content, individuals are increasingly taking advantage of some tools to exert more control over their experiences and what they are willing to share, resulting in more user-based partnerships will formulate. As the transition of traditional forms of marketing to newer forms of integrated marketing, the future for search engines as marketing tools by social media users appears to be very promising in adding contextual content within users’ homepage.

The aim of this paper is to examine the phenomenon of search engine optimization (SEO) as a mechanism for improving libraries' digital content findability on the web.

The study applies web analytical tools, such as Alexa.com, in the collection of data about Canadian libraries' visibility performance in the ranking of search engine results. Concepts from the Integrated IS&R Research Framework are applied to analyze SEO as an element within the Framework.

The results show that certain websites' characteristics do have an effect on how well libraries' websites are ranked by search engines. Notably, the reputation of a library's website and the number of its search engine indexed webpages increase its ranking on SERPs as well as the findability of its digital content.

Most of the existing works on SEO have been confined to popular literature, outside of scholarly academic research in library and information science. Only few studies with a focus on libraries' application of SEO exist. No known study has applied an empirical approach to the examination of relevant libraries' website characteristics to determine their visibility performance on search engine result pages (SERPs). This study identified several website characteristics that can be optimized for higher SERP rankings. It also analyzed the impact of external links, as well as that of the number of indexed webpages by search engines on higher SERP rankings.

The successful provision of context‐awareness in pervasive environments requires the support of autonomic management facilities that provide ways to efficiently acquire and use contextual information. This paper claims that in order to offer viable context‐aware services, the issue of context imperfection and aging as well as the alignment of the context information that is used by a service with the customized service objectives should be taken into account. It presents an approach for managing the selection of context sources considering the freshness and actuality of the available information, and dynamically adapting to any source change and failure. Accordingly, there is no need to know beforehand the context sources to obtain the required information, but a quality‐aware discovery of the sources is envisioned. Finally, the proposed approach allows services to be ported easily to an environment with a different set of context sources.

The purpose of this paper is to discuss Google visibility of five large STM publishers (Elsevier, Emerald Publishing, Springer, Taylor & Francis and John Wiley & Sons) with the aim to focus on and investigate various upcoming current issues and challenges of the publishing industry regarding discoverability, promotion strategies, competition, information-seeking behavior and the impact of new information technologies on scholarly information.

The study is based on data retrieved through two commercial online tools specialized in retrieving and saving the data of the domain's visibility in search engines: SEMrush (“SEMrush – Online Visibility Management Platform”) and Ahrefs (“Ahrefs – SEO Tools & Resources To Grow Your Search Traffic”). All data gathering took place between April 15 and the May 29, 2019.

The study exhibits the significance of Google visibility in the STM publishing industry taking into consideration current issues and challenges of the publishing activity.

This is a “new” trend, certainly of great significance in the publishing industry. The research is conducted in this paper and the theoretical background will be offered to the study of this issue.

This paper aims to describe several methods to expose website information to Web crawlers for providing value-added services to patrons.

This is a conceptual paper exploring the areas of search engine optimization (SEO) and usability in the context of search engines.

Not applicable

This paper explains several methods that can be used to appropriately expose website content and library services to the Web crawlers in such a way that services and content can be syndicated via those search engines.

Context awareness is one of the key aspects of pervasive computing systems. In such systems, a plethora of dynamic context information needs to be constantly retrieved, soundly interpreted, rapidly processed, maintained in various repositories, and securely disseminated. Thus, a flexible, scalable and interoperable context representation scheme needs to be established and solid context management mechanisms need to be adopted, which will perform well in large‐scale distributed pervasive systems. This paper elaborates on the COMPACT context middleware that has been designed to cope with the issues above and saturate pervasive computing environments with context awareness functionality.

Mobile computing research has been focused on developing technologies for handheld devices such as mobile phones, notebook computers, and mobile IP. Today, emphasis is increasing on context‐aware computing, which aims to build the intelligence into mobile devices to sense and respond to the user's context. The purpose of this paper is to present a context‐aware mobile computing model (ContextAlert) that senses the user's context and intelligently configures the mobile phone alert mode accordingly.

The paper proposes a three‐step approach in designing the model based on the embedded sensor data (accelerometer, GPS antenna, and microphone) of a G1 Adriod phone. As adaptivity is essential for context‐aware computing, within this model a new learning mechanism is presented to maintain a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.

The model has been evaluated in many aspects using data collected from human subjects. The experiment results show that the proposed model performs well and yields a promising result.

This paper is distinguished from other previous papers by: first, using multiple sensors embeded in the mobile phone, which is more realistic for detecting the user's context than having various sensors attached to different parts of user's body; second, by being a novel model that uses sensed contextual information to provide a service that better synchronizes the user's daily life with a context‐aware alert mode. With this service, the user can avoid the problems such as forgetting to switch to vibrate mode while in a meeting or a movie theater, and taking the risk of picking up a phone call while driving, and third, being an adaptive learning algorithm that maintains a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.