Vol. 30 · No. 1

Collaborative Working Environments (CWEs) enable an efficient collaboration between professionals, specially those settled in different locations of a company or stakeholders from different companies. This can be of great help for small and medium enterprises (SMEs), as an effective way to share information. However, it can be difficult for SMEs to have access to a fully integrated CWE providing different tools (e.g., videoconferencing, instant messaging, etc.). Currently, they may define a CWE as a combination of heterogeneous and non-integrated tools which are not able to share information between them. An integrated CWE would provide SMEs with the necessary means to collaborate, making information exchange easier.

The lack of a semantic alignment between collaborating small and medium enterprises causes frequent misinterpretations when exchanging information in the form of documents. If these companies are to achieve a seamless semantic alignment by exchanging documents, we should employ a conceptual model which does not rely on agreeing in advance on a centralised standard for document contents and format, but instead allows individual companies to maintain localised ontologies structuring their own documents allowing the companies to automatically establish a semantic alignment between pairs of collaborating companies, taking into account the ripple effects that such an alignment could trigger. In this article we demonstrate how the conceptual model of devolved ontology is engineered and tested to support such a scenario: we show how we have engineered the devolved ontology through a case study, and present experimental results on the document alignment intrinsically needed for this.

In spite of rapid advances in multimedia and interactive technologies, enterprise users prefer to battle with email spam and overload rather than lose the benefits of communicating, collaborating and solving business tasks over email. Many aspects of email have significantly improved over time, but its overall integration with the enterprise environment remained practically the same. In this paper we describe and evaluate a light-weight approach to enterprise email communication analysis and information extraction. We provide several use cases exploiting the extracted information, such as the enrichment of emails with relevant contextual information, social network extraction and its subsequent search, creation of semantic objects as well as the relationship between email analysis and information extraction on one hand, and email protocols and email servers on the other. The proposed approach was partially tested on several small and medium enterprises (SMEs) and seems to be promising for enterprise interoperability and collaboration in SMEs that depend on emails to accomplish their daily business tasks.

A company's ability to flexibly adapt to changing business requirements is one key factor to remain competitive. The required flexibility in people driven processes is usually achieved through ad-hoc workflows which are naturally highly unstructured. Effective guidance in ad-hoc workflows therefore requires a simultaneous consideration of multiple goals: support of individual work habits, classification of unstructured messages, exploration of crowd process knowledge, and automatic adaptation to changes. This paper presents a flexible approach towards the mapping of unstructured messages onto processes as well as patterns for self-adjusting and context-sensitive process recommendations based on the analysis of user behavior, crowd processes, and continuous application of process detection. Specifically, we classify users as eagles (i.e., specialists) or flock. The approach is evaluated in the context of the European research project Commius.

Enterprise 2.0 has been introduced in the SME (Small Medium Enterprise) modifying common organizational and operative practices. This brings the `knowledge workers' to change their working practices through the use of web 2.0 communication tools. Unfortunately, these tools do not allow intercepting and tracing the exchanged data, which can produce a loss of information. This is an important problem in an enterprise context because knowledge of the exchanged information can increase the efficiency and competitiveness of the company. In this article we demonstrate that it is possible to extract this knowledge by an abstraction process of the new operative practices, named collaboration processes, thanks to the use of design patterns. Therefore, we propose design patterns for the collaboration processes useful for modelling typical Enterprise 2.0 activities, having the goal of making more flexible and traceable the use of emerging operative practices.

Consider an orthogonal grid of streets and avenues in a Manhattan-like city populated by stationary sensor modules at some intersections and mobile robots that can serve as relays of information that the modules exchange, where both module-module and module-robot communication is limited to a straight line of sight within the grid. The robots are oblivious and move asynchronously. We present a distributed algorithm that, given the sensor locations as input, moves the robots to suitable locations in the grid so that a connected network of all modules is established. The number of robots that the algorithm uses is worst case optimal.

Collaborative applications offers significant benefits in business sector. Usually, team members need to use several systems to carry out their tasks. What these users need is an environment which permits them to carry out these tasks automatically, considering the flow of information between the different systems and offering interoperability and composition features. Nowadays, Web Services have gained their prominence in providing these both features. On the other hand, the use of Web 2.0 allows to create web applications in which the user constitutes a key element. What we propose in this paper is the combination of both approaches for creating a Collaborative Working Environment (CWE).

Folksonomy and tagging systems, which allow users to interactively annotate a pool of shared resources using descriptive tags, have enjoyed phenomenal success in recent years. The concepts are organized as a map in human mind, however, the tags in folksonomy, which reflect users' collaborative cognition on information, are isolated with current approach. What we do in this paper is to estimate the semantic relatedness among tags in folksonomy: whether tags are related from semantic view, rather than isolated? We introduce different algorithms to form networks of folksonomy, connecting tags by users collaborative tagging, or by resource context. Then we perform multiple measures of semantic relatedness on folksonomy networks to investigate semantic information within them. The result shows that the connections between tags have relatively strong semantic relatedness, and the relatedness decreases dramatically as the distance between tags increases. What we find in this paper could provide useful visions in designing future folksonomy-based systems, constructing semantic web in current state of the Internet, and developing natural language processing applications.

Leukocyte segmentation is one of the essential steps in an automatic leukocyte recognition system. Due to the complexity of the overlapping cell images, methods for leukocyte segmentation are still needed. In this paper, we first construct a combined image by saturation and green channels to extract the nucleus and in turn locate a cursory circular region of the leukocyte. Then the boundary of the leukocyte is represented by the polar coordinate. We determine the overlapping area by polar angle detection. Finally, another combined image is built based on the red and blue channels of the sub image covering the overlap to segment the leukocyte. The paper reports a promising segmentation for 60 microscopic cell images.