Determining the Link and Rate Popularity of Enterprise Process Information

Today's knowledge workers are confronted with a high load of heterogeneous information making it difficult for them to identify the information relevant for performing their tasks. Particularly challenging is thereby the alignment of process-related information (process information for short), such as e-mails, office files, forms, checklists, guidelines, and best practices, with business processes. In previous work, we introduced the concept of process-oriented information logistics (POIL) to bridge this gap. POIL allows for the process-oriented and context-aware delivery of relevant process information to knowledge workers. So far, we have introduced concepts to integrate business processes with process information. A remaining challenge is to identify the process information relevant for a given process context. This paper tackles this challenge and extends our POIL approach with techniques and algorithms for identifying relevant process information. More specifically, we introduce two algorithms for determining the relevance of process information based on their link and rate popularity. We use a scenario from the automotive domain to demonstrate and validate the applicability of our approach

Rural small firms' website quality in transition and market economies

Purpose – The purpose of this paper is to investigate website quality in rural firms in four countries, by using Gonzalez and Palacios's Web Assessment Index (WAI). There is an assertion in the literature that quality is lower amongst rural firms than urban firms, and lower amongst small firms than large firms. The disadvantages of lack of access to skills and economic peripherality in rural areas are attributed to this. Concurrently, there is reason to surmise that the websites of firms in transition economies may be higher quality than those in market economies. The paper aims to explore websites in distinct rural regions to investigate if variation occurs. Design/methodology/approach – To evaluate website quality the WAI was applied to a sample of 60 rural firms representing 15 each in Scotland, New Zealand, Southern Russia and Hunan Province in China. Analysis of the categorical data was performed using a variety of established methods. Findings – The WAI is of use in terms of website quality management. Additionally, comparisons between the quality of websites in the sample of small rural firms with those of large firms in previous studies support the contention that large firms generally have better quality websites. Results also illustrate that there are some differences in website quality between rural small businesses in the different locations. In particular, small rural firms in Hunan Province in China had websites of observable better quality than those elsewhere. The authors conclude that skills, knowledge and infrastructure have a bearing on the sophistication of small firms' websites. Research limitations/implications – Implications include that variation in the rural economy by region prevails as the rural economy is not, as often implied, a homogeneous concept. Practical implications – There are implications in terms of exploring the effects of regulation, culture and infrastructure on rural small to medium-sized enterprises (SMEs). The internet may indeed contribute to rural economies, but only insofar as it is facilitated by infrastructure and access to skills, and by culture and perceived usefulness by business owners. Originality/value – The paper contributes to the understanding of rural entrepreneurship as a heterogeneous concept by comparing practice in four distinct rural regions. It also adds weight to the emerging identification of exogenous factors as being at least as much a factor in determining the use of ICT in rural SMEs as endogenous motivations, skills and resources. </jats:sec

Wireless Communications in the Era of Big Data

The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin

Semantic Modeling of Analytic-based Relationships with Direct Qualification

Successfully modeling state and analytics-based semantic relationships of documents enhances representation, importance, relevancy, provenience, and priority of the document. These attributes are the core elements that form the machine-based knowledge representation for documents. However, modeling document relationships that can change over time can be inelegant, limited, complex or overly burdensome for semantic technologies. In this paper, we present Direct Qualification (DQ), an approach for modeling any semantically referenced document, concept, or named graph with results from associated applied analytics. The proposed approach supplements the traditional subject-object relationships by providing a third leg to the relationship; the qualification of how and why the relationship exists. To illustrate, we show a prototype of an event-based system with a realistic use case for applying DQ to relevancy analytics of PageRank and Hyperlink-Induced Topic Search (HITS).Comment: Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015

Determining citizens’ opinions about stories in the news media: analysing Google, Facebook and Twitter

We describe a method whereby a governmental policy maker can discover citizens’ reaction to news stories. This is particularly relevant in the political world, where governments’ policy statements are reported by the news media and discussed by citizens. The work here addresses two main questions: whereabouts are citizens discussing a news story, and what are they saying? Our strategy to answer the first question is to find news articles pertaining to the policy statements, then perform internet searches for references to the news articles’ headlines and URLs. We have created a software tool that schedules repeating Google searches for the news articles and collects the results in a database, enabling the user to aggregate and analyse them to produce ranked tables of sites that reference the news articles. Using data mining techniques we can analyse data so that resultant ranking reflects an overall aggregate score, taking into account multiple datasets, and this shows the most relevant places on the internet where the story is discussed. To answer the second question, we introduce the WeGov toolbox as a tool for analysing citizens’ comments and behaviour pertaining to news stories. We first use the tool for identifying social network discussions, using different strategies for Facebook and Twitter. We apply different analysis components to analyse the data to distil the essence of the social network users’ comments, to determine influential users and identify important comments

Process-Oriented Information Logistics: Aligning Process Information with Business Processes

During the last decade, research in the field of business process management (BPM) has focused on the design, modeling, execution, monitoring, and optimization of business processes. What has been neglected, however, is the provision of knowledge workers and decision makers with needed information when performing knowledge-intensive business processes such as product engineering, customer support, or strategic management. Today, knowledge workers and decision makers are confronted with a massive load of data, making it difficult for them to discover the information relevant for performing their tasks. Particularly challenging in this context is the alignment of process-related information (process information for short), such as e-mails, office files, forms, checklists, guidelines, and best practices, with business processes and their tasks. In practice, process information is not only stored in large, distributed and heterogeneous sources, but usually managed separately from business processes. For example, shared drives, databases, enterprise portals, and enterprise information systems are used to store process information. In turn, business processes are managed using advanced process management technology. As a consequence, process information and business processes often need to be manually linked; i.e., process information is hard-wired to business processes, e.g., in enterprise portals associating specific process information with process tasks. This approach often fails due to high maintenance efforts and missing support for the individual demands of knowledge workers and decision makers. In response to this problem, this thesis introduces process-oriented information logistics(POIL) as new paradigm for delivering the right process information, in the right format and quality, at the right place and the right point in time, to the right people. In particular, POIL allows for the process-oriented, context-aware (i.e., personalized) delivery of process information to process participants. The goal is to no longer manually hard-wire process information to business processes, but to automatically identify and deliver relevant process information to knowledge workers and decision makers. The core component of POIL is a semantic information network (SIN), which comprises homogeneous information objects (e.g., e-mails, offce files, guidelines), process objects (e.g., tasks, events, roles), and relationships between them. In particular, a SIN allows discovering objects linked with each other in different ways, e.g., objects addressing the same topic or needed when performing a particular process task. The SIN not only enables an integrated formal representation of process information and business processes, but also allows determining the relevance of process information for a given work context based on novel techniques and algorithms. Note that this becomes crucial in order to achieve the aforementioned overall goal of this thesis

Detection of Early-Stage Enterprise Infection by Mining Large-Scale Log Data

Recent years have seen the rise of more sophisticated attacks including advanced persistent threats (APTs) which pose severe risks to organizations and governments by targeting confidential proprietary information. Additionally, new malware strains are appearing at a higher rate than ever before. Since many of these malware are designed to evade existing security products, traditional defenses deployed by most enterprises today, e.g., anti-virus, firewalls, intrusion detection systems, often fail at detecting infections at an early stage. We address the problem of detecting early-stage infection in an enterprise setting by proposing a new framework based on belief propagation inspired from graph theory. Belief propagation can be used either with "seeds" of compromised hosts or malicious domains (provided by the enterprise security operation center -- SOC) or without any seeds. In the latter case we develop a detector of C&C communication particularly tailored to enterprises which can detect a stealthy compromise of only a single host communicating with the C&C server. We demonstrate that our techniques perform well on detecting enterprise infections. We achieve high accuracy with low false detection and false negative rates on two months of anonymized DNS logs released by Los Alamos National Lab (LANL), which include APT infection attacks simulated by LANL domain experts. We also apply our algorithms to 38TB of real-world web proxy logs collected at the border of a large enterprise. Through careful manual investigation in collaboration with the enterprise SOC, we show that our techniques identified hundreds of malicious domains overlooked by state-of-the-art security products

Detecting and characterizing lateral phishing at scale

We present the first large-scale characterization of lateral phishing attacks, based on a dataset of 113 million employee-sent emails from 92 enterprise organizations. In a lateral phishing attack, adversaries leverage a compromised enterprise account to send phishing emails to other users, benefit-ting from both the implicit trust and the information in the hijacked user's account. We develop a classifier that finds hundreds of real-world lateral phishing emails, while generating under four false positives per every one-million employee-sent emails. Drawing on the attacks we detect, as well as a corpus of user-reported incidents, we quantify the scale of lateral phishing, identify several thematic content and recipient targeting strategies that attackers follow, illuminate two types of sophisticated behaviors that attackers exhibit, and estimate the success rate of these attacks. Collectively, these results expand our mental models of the 'enterprise attacker' and shed light on the current state of enterprise phishing attacks

The Impact of Large-scale Employee Share Ownership Plans on Labour Productivity: The Case of Eircom

Large-scale Employee Share Ownership Plans (ESOPs) have been a distinctive characteristic of Irish public enterprise reform, with shareholdings of 14.9 per cent being allocated to employees as part of firm restructuring and privatisation programmes. This paper presents a case study analysis of a large-scale ESOP in Eircom, Ireland’s former national telecommunications operator. We identify changes in labour productivity during the eight years before and after the establishment of the company’s ESOP and use a framework based on Pierce et al. (2001, 1991) to explore the role played by the ESOP. The ESOP was found to play a key role in enabling firm-level reform through concession bargaining and changes in employee relations, and thereby indirectly affecting labour productivity. However, despite the substantial shareholding and influence of the ESOP, we find it has failed to create a sense of psychological ownership among employees, and thereby further impact on productivit