Most recommender systems suggest items to a user that are popular among all users and similar to items the user usually consumes. As a result, a user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected, i.e. serendipitous items. In this paper, we propose a serendipity-oriented algorithm, which improves serendipity through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm and compare it with others, we employ a serendipity metric that captures each component of serendipity, unlike the most common metric.

Since September 2015 at least two major crises have emerged where major industrial companies producing consumer products have been involved. In September 2015 diesel cars manufactured by Volkswagen turned out to be equipped with cheating software that caused NO2 and other emission values to be reduced to acceptable levels while tested from the real, unacceptable values in normal use. In August 2016 reports began to appear that the battery of a new smart phone produced by Samsung, Galaxy Note7, could begin to burn, or even explode, while the device was on. In Nov. 2016 also 34 washing machine models were reported to have caused damages due to disintegration. In all cases, the companies have experienced substantial financial losses, their shares have lost value, and their reputation has suffered among consumers and other stakeholders. In this paper, we study the commonalities and differences in the crisis management strategies of the companies, mostly concentrating on the crisis communication aspects. We draw on Situational Crisis Communication Theory (SCCT). The communication behaviour of the companies and various stakeholders during crisis is performed by investigating the official web sites of the companies and communication in Twitter and Facebook on their own accounts. We also collected streaming data from Twitter where Samsung and the troubled smart phone or washing machines were mentioned. For VW we also collected streaming data where the emission scandal or its ramifications were mentioned and performed several analyses, including sentiment analysis.

Nowadays there are many social media sites with a very large number of users. Users of social media sites and relationships between them can be modelled as a graph. Such graphs can be analysed using methods from social network analysis (SNA). Many measures used in SNA rely on computation of shortest paths between nodes of a graph. There are many shortest path algorithms, but the majority of them suits only for small graphs, or work only with road network graphs that are fundamentally different from social graphs. This paper describes an efficient shortest path searching algorithm suitable for large social graphs. The described algorithm extends the Atlas algorithm. The proposed algorithm solves the shortest path problem in social graphs modelling sites with over 100 million users with acceptable response time (50 ms per query), memory usage (less than 15 GB of the primary memory) and applicable accuracy (higher than 90% of the queries return exact result).

Social media sites have appeared during the last 10 years and their use has exploded all over the world. Twitter is a microblogging service that has currently 320 million user profiles and over 100 million daily active users. Many celebrities and leading politicians have a verified profile on Twitter, including Justin Bieber, president Obama, and the Pope. In this paper we investigate the '‘hundreds of Putins and Obamas phenomenon’ on Twitter. We collected two data sets in 2015 containing 582 and 6477 profiles that are related to the G20 leaders’ profiles on Twitter. The number of namesakes varied from 5 to 1000 per leader. We analysed in detail various aspects of the Putin and Erdogan related profiles. For the first ones we looked into the language of the profiles, their follower sets, the address in the profile and where the tweets were really sent from. For both profile sets we investigated why the accounts were created. For this, we deduced 12 categories based on the information in the profile and the contents of the sent tweets. The research is exploratory in nature, but we tentatively looked into online identity, communication and political theories that might explain emergence of these kinds of Twitter profiles.

Most recommender systems suggest items similar to a user profile, which results in boring recommendations limited by user preferences indicated in the system. To overcome this problem, recommender systems should suggest serendipitous items, which is a challenging task, as it is unclear what makes items serendipitous to a user and how to measure serendipity. The concept is difficult to investigate, as serendipity includes an emotional dimension and serendipitous encounters are very rare. In this paper, we discuss mentioned challenges, review definitions of serendipity and serendipity-oriented evaluation metrics. The goal of the paper is to guide and inspire future efforts on serendipity in recommender systems.

In recent years, there has been an increasing interest in cross-domain recommender systems. However, most existing works focus on the situation when only users or users and items overlap in different domains. In this paper, we investigate whether the source domain can boost the recommendation performance in the target domain when only items overlap. Due to the lack of publicly available datasets, we collect a dataset from two domains related to music, involving both the users’ rating scores and the description of the items. We then conduct experiments using collaborative filtering and content-based filtering approaches for validation purpose. According to our experimental results, the source domain can improve the recommendation performance in the target domain when only items overlap. However, the improvement decreases with the growth of non-overlapping items in different domains.

Organizations establish their own profiles at social media sites to publish pertinent information to customers and other stakeholders. During a long and severe crisis, multiple issues may emerge in media interaction. Positive responses and prompt interaction from the official account of e.g. a car manufacturer creates clarity and reduces anxiety among stakeholders. This research targets the Volkswagen 2015 emission scandal that became public on Sept. 18, 2015. We report its main phases over time based on public web information. To better understand the online interaction and reactions of the company, we scrutinized what information was published on VW’s official web sites, Facebook, and Twitter profiles and how the image of the company developed over time among various stakeholders. To investigate this, Twitter and Facebook data sets were collected, cleaned, and analysed. We also compared this crisis in several respects with the Toyota recall crisis in 2010-2011 that was caused by sticking accelerator pedals and floor mats, as well as the GM crisis in 2014 that was caused by faulty ignition switches. Further we compare our findings with the Malaysian airline crisis that was caused by the disappeared flight MH370 and downed MH14.

Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in both accuracy and efficiency in comparison with pairwise CF. In ListCF, each user is represented as a probability distribution of the permutations over rated items based on the Plackett-Luce model, and the similarity between users is measured based on the Kullback--Leibler divergence between their probability distributions over the set of commonly rated items. Given a target user and the most similar users, ListCF directly predicts a total order of items for each user based on similar users’ probability distributions over permutations of the items. Besides, we also reveal insightful connections among pointwise, pairwise, and listwise CF algorithms from the perspective of the matrix representations. In addition, to make our algorithm more scalable and adaptive, we present an incremental algorithm for ListCF, which allows incrementally updating the similarities between users when certain user submits a new rating or updates an existing rating. Extensive experiments on benchmark datasets in comparison with the state-of-the-art approaches demonstrate the promise of our approach.

The paper addresses the problem of coverage testing of industrial automation software represented in the IEC 61499 standard, one of the recent standards for distributed control system design. Contrary to model-based testing (MBT), the paper focuses on implementation coverage, not model coverage. An approach based on evolutionary algorithms is presented which generates coverage test suites for both basic and composite IEC 61499 function blocks. It employs two third-party tools, FBDK and EvoSuite. The evaluation of the approach was performed on a set of control applications for two lab-scale demonstration plants. Results show that the approach is applicable and shows good performance at least on basic function blocks. The generated tests suites helped to discover several unreachable system parts, which pinpointed errors in the systems under test.

Recently, ranking-oriented collaborative filtering (CF) algorithms have achieved great success in recommender systems. They obtained state-of-the-art performances by estimating a preference ranking of items for each user rather than estimating the absolute ratings on unrated items (as conventional rating-oriented CF algorithms do). In this paper, we propose a new ranking-oriented CF algorithm, called ListCF. Following the memory-based CF framework, ListCF directly predicts a total order of items for each user based on similar users' probability distributions over permutations of the items, and thus differs from previous ranking-oriented memory-based CF algorithms that focus on predicting the pairwise preferences between items. One important advantage of ListCF lies in its ability of reducing the computational complexity of the training and prediction procedures while achieving the same or better ranking performances as compared to previous ranking-oriented memory-based CF algorithms. Extensive experiments on three benchmark datasets against several state-of-the-art baselines demonstrate the effectiveness of our proposal.

In this article we describe a framework (DEGA-Gen) for the application of distributed genetic algorithms for detection of communities in networks. The framework proposes efficient ways of encoding the network in the chromosomes, greatly optimizing the memory use and computations, resulting in a scalable framework. Different objective functions may be used for producing division of network into communities. The framework is implemented using open source implementation of MapReduce paradigm, Hadoop. We validate the framework by developing community detection algorithm, which uses modularity as measure of the division. Result of the algorithm is the network, partitioned into non-overlapping communities, in such a way, that network modularity is maximized. We apply the algorithm to well-known data sets, such as Zachary Karate club, bottlenose Dolphins network, College football dataset, and US political books dataset. Framework shows comparable results in achieved modularity; however, much less space is used for network representation in memory. Further, the framework is scalable and can deal with large graphs as it was tested on a larger youtube.com dataset.

This paper describes traces of user activity around a alleged online social network profile of a Boston Marathon bombing suspect, after the tragedy occurred. The analyzed data, collected with the help of an automatic social media monitoring software, includes the perpetrator's page saved at the time the bombing suspects' names were made public, and the subsequently appearing comments left on that page by other users. The analyses suggest that a timely protection of online media records of a criminal could help prevent a large-scale public spread of communication exchange pertaining to the suspects/criminals' ideas, messages, and connections.

Nowadays, WWW contains a number of social media sites, which are growing rapidly. One of the main features of social media sites is to allow to its users creation and modification of contents of the site utilizing the offered WWW interfaces. Such contents are referred to as user generated contents and their type varies from site to site. Social media sites can be modeled as constantly evolving multirelational directed graphs. In this paper we discuss persistent data structures for such graphs, and present and analyze queries performed against the structures. We also estimate the space requirements of the proposed data structures, and compare them with the naive "store each complete snapshot of the graph separately". We also investigate query performance against our data structure. We present analytical estimation results, simulation results, and discuss its performance when it is used to store entire contents of Live journal.

In the developed world health care sector has used for tens of years information systems in their daily activities. Soon after the Internet usage began to spread to the societies mid 1990'ies the sector began to ponder how to offer services over the web to patients. The USA and the EU began to discuss eHealth scenarios, and many services are now offered, including appointments to doctors and nurses, virtual doctors, and electronic prescriptions. Electronic patient records are widely utilized could also be retrieved by patients and other health care personnel, but due to technical, organizational and legal restrictions this is not yet reality. Mobile networks and high-end mobile terminals are as powerful as laptops were a few years ago and could be used to access and store pertinent health information. In this article we discuss architectural choices that would facilitate the usage of the collected personal health care information, and their pros and cons. We mainly base our findings on the situation in Finland. We contrast, though, the findings with the situation in Cameroon, where the ICT infrastructure is weak and the ICT infrastructure in the health care could more strongly rely on mobile networks and emerging smart terminals.

The number of mobile devices has exceeded four billions and is still growing. Especially in developing countries mobile devices are often the only access to Internet and digital services. In the most developed countries laptops, Wi-Fi and faster and faster wireless telecom networks have for long time made mobile access to various digital services possible while on the move. Still, large and instant mobile communities can only rely on more portable devices, such as mobile phones. In this paper we will analyze various mobile communities and the support they are offered by the social media sites. We will discuss the phenomena encountered in developing countries, like how the mobile technology transforms the rural areas. We will also cite some recent statistics about mobile penetration. We take a closer look at the development in Pakistan and surrounding Asian countries.

The number of mobile subscribers in the world is soon reaching the three billion mark. According to the newest estimates, majority of the subscribers are already in the developing countries, whereas the number of subscribers in the industrialized countries is about to stagnate around one billion. Because especially in the developing countries the only access to Internet are mobile devices, developing high quality services based on them grows in importance. Ontologies are an important ingredient towards more complicated mobile services and wider usage of mobile terminals. In this article, we first discuss ontology and epistemology concepts in general. After that, we review ontologies in the computer science field and introduce mobile ontologies as a special category of them. It seems reasonable to distinguish between two orthogonal categories, mobile domain ontologies and flowing ontologies. The domain of the former one is in some sense related with mobility, whereas the latter ones are able to flow from computer to computer in the network. We then discuss the creation issues, business aspects, and intellectual property rights (IPR), including patentability of mobile ontologies. We also discuss some basic requirements for computer systems architectures that would be needed to support the usage of mobile ontologies.

The number of mobile subscribers in the world is soon reaching the three billion mark. According to the newest estimates, majority of the subscribers are already in the developing countries, whereas the number of subscribers in the industrialized countries is about to stagnate around one billion. Because especially in the developing countries the only access to Internet are mobile devices, developing high quality services based on them grows in importance. Ontologies are an important ingredient towards more complicated mobile services. In this paper we refine the taxonomy for mobile ontologies and discuss their creation, business models, maintenance and intellectual property rights (IPR).

The number of mobile terminals is continuously increasing in the world, although in many developed countries the market has saturated. Thus, the market can only grow if new service types are offered to the mobile terminals. One emerging technology that might make this possible is semantic web services. At the core of this technology are ontologies that are necessary for automatic discovery and composition of the services. In this paper we discuss how mobility affects the architectural considerations of semantic web service platform and particularly ontology management. We rely on reference architecture for Semantic Web Services in our work.

Mobile phones and other small and powerful portable devices have revolutionized personal communication and affected the lifestyles of the people in the industrialized world. Following credible estimates, in a few years there will over two - billions of such portable devices in use. An emerging trend is the electronic commerce performed using mobile terminals over wireless networks, often called mobile commerce or M-commerce. Mobile commerce environments are characterized by high complexity, including myriads of technical and organizational aspects. This property makes it difficult to distinguish the more fundamental issues, structures, and concepts in mobile commerce from the hype. To capture the fundamental aspects and objects of mobile commerce environments, we have developed a model. It covers fundamental structures and persistent entities of the M-commerce environment, as well as their relationships. Rather than providing technical details of M-commerce environments, our aim is to model invariant properties that will evidently persist for years to come. Making use of the abstraction capabilities provided by the object-oriented approach, the model is represented by OO structure diagrams.Structurally, we distinguish four spheres of concern: Regulatory Frameworks, Business Models, Enabling Technologies, and the Global Infrastructure. These are dependent on each other, but have a relative independence and development logic that is different in each sphere of concern. In addition, the development logic is different in different regions of the world. The leading Regulatory Areas are currently Far-East (Japan, South Korea), Europe (European Union), and USA. These are analyzed in the light of a few examples.The material on which the keynote is mainly based has been published in [1] and [2].

Purpose To report the work on the design of an integrated identity verification system architecture aimed at approaching high verification accuracy, continuous security, and user‐friendliness. Design/methodology/approach The reported research corresponds to the building process in the design science research paradigm. The requirements to an identity verification system are defined and used in the selection of architecture components. Furthermore, various issues affecting the suitability of component distribution between a terminal and a remote server are considered. Findings In order to meet the stated requirements, in the proposed architecture static and dynamic identity verification is combined. The use of the dynamic part enables continuous and user‐friendly verification, while the static part is responsible for accurate verification. A suitable distribution of architecture components between the terminal and the remote server is proposed. Research limitations/implications The proposed architecture represents a specification that corresponds to the computational viewpoint of the reference model for open distributed processing. Other specifications, such as engineering or technological specifications, which are needed for successful implementation of the system, are not provided in the paper. Practical implications The paper provides a specification of the integrated identify verification system architecture that can be utilised during further design and subsequent implementation of the system. Originality/value While available approaches to identity verification in a mobile environment concentrate mainly on connectivity identity verification (employed in accessing communication services), the proposed architecture focuses on application‐level identity verification needed to access application‐level resources, remotely or locally on the terminal.

Workflow techniques have gained a lot of attention as a means to support advanced business applications such as cooperative information systems and process re-engineering but also as a means to integrate legacy systems. Inter-task dependencies, described separately from the other parts of the workflow, have been recognized as a valuable method in describing certain restrictions on the executions of workflows. In this paper, we study the issue of pre-analysing and enforcing inter-task dependencies. The protocol and the theory behind it are presented, along with examples and discussions on ways to improve the performance. The idea is to present the meaning of a dependency through an automaton which accepts the sequences of events tied by the dependency through an automaton which accepts the sequences of events tied by the dependency. We prune from the automata certain paths that cannot be followed due to the conflicting paths in other automata and record the feasible event sequences in a special data structure to be used during run-time. We show the correctness of the algorithms and also show that our run-time algorithm is linear, whereas the original approach suggested by MCC in Refs. 5 and 6 is exponential, when resolution of one event is concerned.

Workflowtechniques have gained a lot of attention as a means to support business process r~engineering but also as a means to integrate legacy systems.Most workflow models view the applications as a fixed set of tasks.In this paper we analyse inter-organisational application domains and analyse properties for transactional workflows and systems supporting them.We study a workflow model for the applications where job step instances cannot be fixed in advance.We analyse requirements arising horn this kind of environments through a particular application, and introduce special modelling components to support these requirements.We also develop the concept of C-unit to cope with concurrency anomalies and recovery.

Algorithms for scheduling of distributed transactions in a heterogeneous multidatabase, in the presence of failures, are presented. The algorithms of prepare certification and commit certification protect against serialization errors called global view distortions and local view distortions. View serializable overall histories are guaranteed in the presence of most typical failures. The assumptions are, among others, that the participating database systems produce rigorous histories and that no local transaction may update the data accessed by a global transaction that is in the prepared state. The main advantage of the method, as compared to other known solutions, is that it is totally decentralized.>