Showing papers presented at "International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management in 2017"

The Knowledge Managment Capability of High-Technology Enterprises.

Abstract: Improving the knowledge management (KM) capability in order to gain sustainable competitive advantages has emerged as an important strategy for addressing recurring problems in a new product development such a long time-to-market, riskiness and high development costs. Synthesizing prior theoretical research in innovation management, competitive advantages, KM and practical activities of high-technology engineering enterprises it is posited that innovation, engineering processes and organizational culture are important antecedents of KM capability. However, it is vague whether the KM capability as a mediator affects competitive advantages. The aim of the paper is to explore the impact of the KM capability in hightechnology engineering enterprises. To achieve this aim we have contributed an empiric research in which 50 high-technology engineering enterprises of Russia were involved. The regression analysis is applied to analyze the obtained empiric data. Among the three selected antecedents the engineering processes have the most impact on the KM capability. The research hasn’t proved the mediating role between the KM capability and competitive advantages because of relative novelty of this phenomenon to Russian hightechnology enterprises.

End-users Co-create Shared Information for a More Complete Real-time Maritime Picture

Abstract: European Union Member States are working towards an integrated maritime surveillance and deeper information sharing and implementation of Common Information Sharing Environment. Value networks aiming at co-creation, need active facilitation, and relevant platforms for open cooperation. This study analysed scenario analytics, and narrative documents from projects CoopP, CISE, and MARISA by using a Data Extraction Table to classify both objects and phenomenon relevant to European maritime information sharing systems. The object and phenomenon rows are grouped under a European Coast Guard Functions, CGFs framework, to better understand their occurrence and interdependencies. This paper finds that objects and phenomena need to be continuously evaluated against evolving risk and treat scenarios and end-user needs. Shared maritime information systems need to include tools for continuous self-revaluation. Added complexity may greatly reduce the time to value creation and innovation, which in this context is the ability to create greater common knowledge, learning, and value. Thus, faster and more widely shared information on objects and phenomena result in an accurate Recognized Maritime Picture, which supports threat assessment, asset and operations planning, and sharing of resources for added safety and security on the European maritime domain.

Collaborative Networks in the Portuguese Footwear Sector and the Cluster of Felgueiras.

Abstract: Globalization and the rapid market changes increased the perception in the Portuguese footwear industry that success in the value chain is closely tied to information sharing, the creation and development of collaborative networks, and the management of the knowledge of the various partners. Business to Business (B2B) and eCommerce (eC) are a key opportunity, and at the same time, a challenge for contemporary companies. We believe that the insights provided in this paper allow theory and practice to better understand the reasons for the success of the Portuguese footwear industry and of its key cluster of Felgueiras. Based on the research conducted, we argue that there is a lack of B2B-eC initiatives in the footwear industry and the existing ones are still incipient. Furthermore, the existence of only one platform that to some extent addresses B2B-eC, also indicates that there is a need for greater research and development of approaches/technology allowing companies to explore opportunities to collaborate and negotiate among themselves.

Information Capture and Knowledge Sharing Systems in the Field of Library and Information Science: The Case of MEDLIB-L in Medicine

Abstract: Professionals using the Internet have various tools with which to capture and share information. Email discussion lists, despite their age, are still one of the main applications that telematic networks use for information to be shared in the social media field. They have not lost their validity even though the arrival of numerous applications associated with other types of social media, such as social networks, microblogging networks, wikis, etc., was often thought to augur their demise. Also, the new culture of Knowledge management, in which people share data, knowledge, and experiences, has, with its technological bases, become an indispensable tool for human interaction. This paper presents the results of a study applied to the medical sector which surveyed the MEDLIB-L discussion list users specialists in medical information. The primary aim was to determine the usefulness of the various tools they use (social media, literature alert systems, syndication RSS, search engine alerts, new content trackers) to capture and share information of interest and to serve as means of training and learning. A further aim was to determine the quality and usefulness of the messages sent by the professionals of information management in medicine to the list and the usefulness of its message archiving system.

Satisfaction with E-Government Portals: Perspective of Senior Citizens

Abstract: This study aims to investigate the level of user satisfaction with the services provided by e-government portals and to examine the effect of perceived value and social influence on senior citizens’ satisfaction and their continuous use intentions. Through a questionnaire survey, primary data are collected from 123 senior citizens who use e-government portals. The findings show that senior citizens are moderately satisfied with the services provided by e-government portals and positive on their continuous use intentions. Egovernment portals in the area of health and tourism are used more heavily than others. Both perceived value and social influence relate positively with senior citizens’ satisfaction, but perceived value has a relatively stronger effect on satisfaction than social influence. Senior citizens’ satisfaction also positively affects their continuous use intentions of e-government portals. The findings enhance the understanding of e-government portals that senior citizens consider valuable and additionally, highlight the role of social influence in affecting their satisfaction and subsequently their continuous use intentions.

Factors Influencing the Participation of Information Security Professionals in Electronic Communities of Practice

Abstract: The purpose of this study is to contribute to a better understanding of the current status of the participation of the information security professionals (ISPs) in the electronic communities of practice (eCoP) in the information security (IS) domain in Norway. An online survey is conducted with 56 ISPs working in Norway to investigate this issue. This study used the logistic regression as a statistical technique to formulate the results and findings. The probability of an ISP being a user of eCoP is tested with demographic data, nature of the job, and the knowledge sharing preference. Furthermore, the determinants of the knowledge sharing theories, i.e., the theory of planned behavior, the motivation theory, and perceived trust theory are used to test our statistical model. The findings of this study are useful to get the initial insight into the determinants that influence the participation of ISPs in eCoP in Norway.

Predictive model based on sentiment analysis for peruvian smes in the sustainable tourist sector

Abstract: In the sustainable tourist sector today, there is a wide margin of loss in small and medium-sized enterprise (SMEs) because of a poor control in logistical expenses. In other words, acquired goods are note being sold, a scenario which is very common in tourism SMEs. These SMEs buy a number of travel packages to big companies and because of the lack of demand of said packages, they expire and they become an expense, not the investment it was meant to be. To solve this problem, we propose a Predictive model based on sentiment analysis of a social networks that will help the sales decision making. Once the data of the social network is analyzed, we also propose a prediction model of tourist destinations, using this information as data source it will be able to predict the tourist interest. In addition, a case study was applied to a real Peruvian tourist enterprise showing their data before and after using the proposed model in order to validate the feasibility of

Empowering Capability for Innovation in IT Organizations - A Confluence of Knowledge for Continual Organizational Learning.

Abstract: In IT based business model innovations, emerging technologies introduce disruption into processes and organizational capabilities that could be difficult to overcome. IT services organizations must maintain their IT capabilities of innovation integration in order to exploit it internally and for their customers. Using the literature on resource based views as a grounding for organizational capabilities, this paper introduces a model of continual organizational learning that empowers IT organizations for innovation integration. Through indepth case studies conducted at IT services companies, this exploratory research identifies mechanisms of knowledge management are required to transform IT organizations to a lever rather than a barrier to integrating innovation based on emerging technologies. The study succinctly presents the convergence of knowledge assets through a cyclic process that empowers IT organization to embrace innovation.

Itemset Hiding under Multiple Sensitive Support Thresholds.

Abstract: Itemset mining is the challenging step of association rule mining that aims to extract patterns among items from transactional databases. In the case of applying itemset mining on the shared data of organizations, each party needs to hide its sensitive knowledge before extracting global knowledge for mutual benefit. Ensuring the privacy of the sensitive itemsets is not the only challenge in the itemset hiding process, also the distortion given to the non-sensitive knowledge and data should be kept at minimum. Most of the previous works related to itemset hiding allow database owner to assign unique sensitive threshold for each sensitive itemset however itemsets may have different count and utility. In this paper we propose a new heuristic based hiding algorithm which 1) allows database owner to assign multiple sensitive threshold values for sensitive itemsets, 2) hides all user defined sensitive itemsets, 3) uses heuristics that minimizes loss of information and distortion on the shared database. In order to speed up hiding steps we represent the database as Pseudo Graph and perform scan operations on this data structure rather than the actual database. Performance evaluation of our algorithm Pseudo Graph Based Sanitization (PGBS) is conducted on 4 real databases. Distortion given to the nonsensitive itemsets (information loss), distortion given to the shared data (distance) and execution time in comparison to three similar algorithms is measured. Experimental results show that PGBS is competitive in terms of execution time and distortion and achieves reasonable performance in terms of information loss amongst the other algorithms.

Prediction and Trading of Dow Jones from Twitter: A Boosting Text Mining Method with Relevant Tweets Identification

Abstract: Previous studies claim that financial news influence the movements of stock prices almost instantaneously, however the poor foreseeability of news limits their possibility of predicting the stock price changes and trading actions. Recently complex sentiment analysis techniques have also showed that large amount of social network posts can predict the price movements of the Dow Jones Industrial Average (DJIA) within a less stringent timescale. From the idea that the contents of social posts can forecast the future stock trading actions, in this paper we present a simpler text mining method than the sentiment analysis approaches, which extracts the predictive knowledge of the DJIA movements from a large dataset of tweets, boosting also the prediction accuracy by identifying and filtering out irrelevant/noisy tweets. The noise detection technique we introduced improves the initial effectiveness of more than 10%. We tested our method on 10 millions twitter posts spanning one year, achieving an accuracy of 88.9% in the Dow Jones daily predictions, which, to the best of our knowledge, improves the best literature result based on social networks. Finally we have used the prediction method to drive the DJIA buy/sell actions of a trading protocol; the achieved return on investments (ROI) outperforms the state-of-the-art.

Empowering IT Organizations Through a Confluence of Knowledge for Value Integration into the IT Services Firm’s Business Model

Abstract: Challenges in operationalizing business innovation based on information technology (i.e. advancing new technology from the lab to the business operations) affect the ability of IT organizations to implement and effectively exploit these technologies. In IT services firms, these challenges are often linked to conflicting priorities, integration issues, inadequate infrastructure capabilities and the availability of the required knowledge/skills. Sometimes insurmountable these challenges leave the firm incapable to incorporate emerging information technologies into their business model. At the intersection of knowledge-based theory of the firm and the theory of dynamic capabilities, the study draws insight from the two cases in IT services companies. We seek to understand mechanism required to manage the flow knowledge assets for successful integration of innovation, while assimilating the tacit knowledge of the customer as a major component in the value integration. The study has far‐reaching implications for practice and produces interesting opportunities for further research.

An Approach to Designing Software Engineering Thesis Papers.

Abstract: Thesis development proves most complicated for students, as it implies more than one final work product and involves facing deadlines. One of the most challenging aspects here is writing the thesis paper. Software engineering is marked by specific difficulties, since students focus on the software development and neglect other aspects, first of all, the thesis paper writing. Hence thesis paper writing demands significant support from the university. This paper presents a method of managing the thesis paper writing process for software engineering undergraduates. Mind mapping is used for the early design, fast feedback, and a wide discussion of the thesis paper plans. The method is implemented as a one semester course for last year undergraduates. The evaluation conducted indicates a significant increase in the quality of thesis papers.

Knowledge Creation in Cross-Border and Cross-Sectoral Collaborations : Exploring EU Externally Funded Security Research and Innovation Projects as Communities of Practice

Abstract: The purpose of this paper is to explore how knowledge creation in EU externally funded security Research and Innovation (R&I) projects can be understood through the concept of community of practice (CoP). A multiple case study design was used to examine EU R&I projects with the Wenger’s identity-practice framework that characterizes conventional CoPs. Qualitative data analysis was conducted based on rich empirical data collected during June 2015 – July 2017. The results of the study suggested that the EU R&I project consortium is a knowledge community in its own right, which knowledge creation cannot be fully understood if analysed as traditional project organizations. CoP framework can provide a meaningful way to investigate how explicit and tacit knowledge is created and shared within a project consortium and across different consortiums. Namely the engagement in different phases of the work undertaken by the project consortium can help to understand how the socialization facilitates knowledge creation and transfers, as well as identity development as the project evolves. As a whole, CoP theory can provide new insight in the knowledge creation in cross-border and cross-sectoral collaborations. It can provide a meaningful way to explore how the knowledge is emerged through a practice in project consortiums before, during, and after

Identification of Relevant Hashtags for Planned Events Using Learning to Rank

Abstract: Lots of planned events (e.g. concerts, sports matches, festivals, etc.) keep happening across the world every day. In various applications like event recommendation, event reporting, etc. it might be useful to find user discussions related to such events from social media. Identification of event related hashtags can be useful for this purpose. In this paper, we focus on identifying the top hashtags related to a given event. We define a set of features for (event, hashtag) pairs, and discuss ways to obtain these feature scores. A linear aggregation of these scores is used to finally output a ranked list of top hashtags for the event. The aggregation weights of the features are obtained using a learning to rank algorithm. We establish the superiority of our method by performing detailed experiments on a large dataset containing multiple categories of events and related tweets.

Technological Communication Tools in Use - The Shape of Knowledge Shared within Software Development Teams.

Abstract: Knowledge is a strong competitive source for organizations, giving sustainability, and generating long-term success to them. Communication is the basis of the software project since it provides a way to share knowledge among development team members. Technological tool adoption is one of the strategies to improve communication within software development teams and provide the knowledge sharing among its members. Thus, this paper aims to investigate the shape of the knowledge shared by software development teams through technological communication tools (tech-comm-tools). We collected data through a structured questionnaire and face-to-face interviews. The findings point out the team knowledge is shared by mean texts, photos, and videos according to four categories, such as notification, issues, support to clients, and

SME Managers' Causal Beliefs of the Role of Inter-organizational Learning in Supply Chain: An Empirical Study.

Abstract: This study answers the call for empirical research on how managers ́ perceive their business network. Here we focus on SME managers ́ reasoning regarding inter-organizational learning. We combine the concept of managerial cognition with inter-organizational learning (IOL) theories, and study CEOs ́ cognitive maps to find out how managers deduce the effects of learning to their company ́s performance and success. The data consists of interviews of five CEOs of small and medium sized companies (SMEs) representing technology industries in Finland. The SMEs also represented different positions in their supply chains: one subcontractor, one hub, and three companies in the middle of the supply chain. Interviews with the CEOs revealed strong learning intent with effects of relational learning and interactive learning. Learning was described to occur both upstream and downstream of the supply chain, and the CEOs perceived the effects of learning to be beneficial both for the relationships and for the individual companies. We contribute to the knowledge of the role of IOL and CEOs ́ cognitive reasoning paths concerning its effects on company ́s performance. By using laddering, a rarely used interview technique in management and organization research, together with managerial cognitive maps, our study provides also methodological contributions.

GeCoLan: A Constraint Language for Reasoning About Ecological Networks in the Semantic Web

Abstract: Ecological Networks (ENs) describe the structure of existing real ecosystems and help planning their expansion, conservation and improvement. While various mathematical models of ENs have been defined, to our knowledge they focus on simulating ecosystems, but none of them deals with verifying whether any transformation proposals, as those collected in participatory decision-making processes for public policy making, are consistent with land usage restrictions.

Transfer Learning in Sentiment Classification with Deep Neural Networks

Abstract: Cross-domain sentiment classifiers aim to predict the polarity (i.e. sentiment orientation) of target text documents, by reusing a knowledge model learnt from a different source domain. Distinct domains are typically heterogeneous in language, so that transfer learning techniques are advisable to support knowledge transfer from source to target. Deep neural networks have recently reached the state-of-the-art in many NLP tasks, including in-domain sentiment classification, but few of them involve transfer learning and cross-domain sentiment solutions. This paper moves forward the investigation started in a previous work [1], where an unsupervised deep approach for text mining, called Paragraph Vector (PV), achieved cross-domain accuracy equivalent to a method based on Markov Chain (MC), developed ad hoc for cross-domain sentiment classification. In this work, Gated Recurrent Unit (GRU) is included into the previous investigation, showing that memory units are beneficial for cross-domain when enough training data are available. Moreover, the knowledge models learnt from the source domain are tuned on small samples of target instances to foster transfer learning. PV is almost unaffected by fine-tuning, because it is already able to capture word semantics without supervision. On the other hand, fine-tuning boosts the cross-domain performance of GRU. The smaller is the training set used, the greater is the improvement of accuracy.

Should User-generated Content be a Matter of Privacy Awareness? - A Position Paper.

Abstract: Social Network Sites (SNSs) like Facebook or Twitter have radically redefined the mechanisms for social interaction. One of the main aspects of these platforms are their information sharing features which allow user-generated content to reach wide and diverse audiences within a few seconds. Whereas the spectrum of shared content is large and varied, it can nevertheless include private and sensitive information. Such content of sensitive nature can derive in unwanted incidents for the users (such as reputation damage, job loss, or harassment) when reaching unintended audiences. In this paper, we analyse and discuss the privacy risks of information disclosure in SNSs from a user-centred perspective. We argue that this is a problem of lack of awareness which is grounded in an emotional detachment between the users and their digital data. In line with this, we will discuss preventative technologies for raising awareness and approaches for building a stronger connection between the users and their private information. Likewise, we encourage the inclusion of awareness mechanisms for providing better insights on the privacy policies of SNSs.

Robust Single-Document Summarizations and a Semantic Measurement of Quality

Abstract: The goal of this paper is to generate an effective summary for a given document with specific realtime requirements. We use the softplus function to enhance keyword rankings to favor important sentences, based on which we present a number of extractive summarization algorithms using various keyword extraction and topic clustering methods. We show that our algorithms not only meet the realtime requirements but also yield the best ROUGE scores on DUC-02 over all previously-known algorithms. We also evaluate our summarization methods over the SummBank dataset and other datasets to ensure that our methods are robust. Experiments show that summaries generated by our methods achieve higher or about the same ROUGE scores than extractive summaries generated by human evaluators. Moreover, we define a semantic measure based on word-embedding using Word Mover’s Distance to evaluate the quality of summaries without human-generated benchmarks. We show that for our algorithms, the orderings of the ROUGE scores and the scores under the new measure are highly comparable, suggesting that this new measure may serve as a viable alternative for measuring the quality of a summary.

Towards Knowledge and Data Fusion Community : Knowledge Sources, Transfers and Co-Creation in Externally Funded Research and Development Consortiums

Abstract: One of the most important functions of every externally funded research consortium, e.g., FP and HORIZON, ACADEMY and TEKES, is to contribute to knowledge transfers and research and development related continuums between research programmes, higher education institutions, world of work, authorities, and actors of regional-national-union policy development and decision making. This empirical study is intended to the data and knowledge which can be transferred and co-created with participators as well as to the partnership relations of research consortium that can exploit parallel the data and knowledge sources, transfers, future continuums and high-value impacts in research-development-innovation processes. In this study, user and stakeholders needs, proactive views and operational scenarios stimulates the knowledge and data fusion user community to foster proactive involvement of stakeholders following a user-stakeholdercentric approach in the validation and utilisation of knowledge sources and transfers, addressing to: user and stakeholder needs and requirements, user experience, animated and interactive design, legacy systems connectivity, interdisciplinary and co-creativity over vary silos and mutual trust building.

Managing Production Complexity with Intelligent Work Orders.

Abstract: Progress of Industrial Internet of Things is rapidly increasing the amount of data collected from manufacturing operations. This data can be utilized to control and improve production systems in various ways. Production control systems play a key role in realizing the potential cost savings and productivity increase. Companies are required to manage increasing complexity while shortening response times to changes. A concept of Intelligent Work Order (IWO) is proposed to assist in these challenges. It supports local or distributed decision-making, and decreases integration complexity between different factory IT-systems. IWOs also increase information visibility at the shop floor. The IWO structure and functionality are described with a discussion of the benefits of the approach.

A Risk Diagnosing Methodology Web-based Tool for SME’s and Start-up Enterprises

Abstract: This work presents a risk diagnosing methodology (RDM) web-based tool, that can provide to Small and Medium Enterprises (SME’s) the capability to identify, evaluate and manage the risks associated with a company’s idea development project portfolio. This tool was conceived to support successful innovative product/service development projects, from its idealization to its commercialization, and to encourage SME’s on systematic use of risk management approaches in order to increase their successful rates. This paper also includes a brief literature review of some of the risk management tools and models available to SME’s, as well as comparative analyses of the identified similar tools.

Smart Access to Historical Archives based on Rich Semantic Metadata

Abstract: Documentary heritage about social and political history of the 20th Century could be an important support for citizens awareness, provided that it is not endangered by the lack of effective access and management tools. In this paper we present a work that is part of the Harlock'900 project and aims at showing how a rich semantic representation, based on ontologies and Semantic Web standards, can enable an innovative and user-friendly access to resources stored in historical archives. In particular, we present a web application enabling users to explore events, places and people mentioned in archival resources. The application relies on a semantic layer  including a computational ontology and a RDF triplestore, and provides a User Interface that supports the navigation through highly interconnected data, offering different possible exploration paths. We also report the encouraging feedback obtained by a preliminary evaluation based on a domain expert walkthrough the app.

e-Marketing of Egovernment Initiatives: A Case Study of Pakistan

Abstract: The research study examines the role of electronic (e)-marketing to improve the citizen satisfaction about government initiatives. E-marketing is a new emerging concept and recognized internationally as an enabler towards achieving good governance while improving the citizens’ satisfaction. Government initiated many projects for improving the infrastructure and living standard of its citizens but there is inertia in these projects and government has achieved milestone on papers. However, government can improve its progress and bring transparency in its projects through e-marketing. In this way, citizens can play important role in the progress of government projects. This research presented the SWOT analysis and found that e-marketing of government initiatives is critical in twenty first century, it can help the public sector to take all stakeholders on board, which improve citizens satisfaction level about government initiatives. This research study concluded that federal government of Pakistan should focus on e-marketing in order to achieve its objectives effectively and improve the public sector services to its citizens.

Linking Knowledge Creating Capabilities, IT Business Value and Digital Business Value: An Exploratory Study in Japanese SMEs.

Abstract: Aiming to address the increasing focus on digital technologies and the continuous concern of Knowledge Management (KM) performance, this study explores the relationship between 'Knowledge Creating Capabilities', 'IT business value' and 'Digital business value'. The latter two concepts are re-defined as the achievement of business objectives by the use of IT or digital technologies in a balanced scorecard approach. The concepts of 'Knowledge Creating Capabilities' and 'Balanced SECI' are leveraged. Balanced SECI (Riera, Senoo and Iijima, 2009) refers to the balance of the four knowledge creation processes from Nonaka and Takeuchi’s SECI model (1995). This framework is applied to Japanese small and medium enterprises. A positive relationship between the achievement of business objectives by IT and the achievement using digital technologies was verified. On the other hand, although a relationship of 'Balanced SECI' with 'IT Business Value' or 'Digital Business Value' was not statistically significant; the observations showed that higher levels of 'Balanced SECI' were negatively related to the achievement of Financial, Customer and Business Processes types of business objectives and; positively related to Learning & Growth. Analysis from each SECI process confirmed such behaviour.

Economic Success of Employment and Revenue Generated from Research Commercialization Activities.

Abstract: The concept of entrepreneurial universities has gained more attention from policy makers and academics due to its perceived prospect of contributing to innovation and economic growth. Spin offs companies helps universities to commercialize their knowledge and technological developments. The commercialization of academic research results through academic spin-offs is becoming an important and increasingly reliable source of revenue for universities. Universities also contribute to employment creation when they establish new spin off firms or help to revamp existing ones. Universities and industries usually cooperate and engagement themselves through joint research projects and this helps universities to commercialize and exploit research results by way of patents licensing and spin-offs. The main focus of this paper is to establish the relationship that exits between the economic successes of spin offs in terms of employment and revenue generation and their spillover effects of contributing to regional growth and development. Using the linear regression method, this paper has demonstrated that, spin offs firms contribute better to employment creation than revenue generation. Spin offs that are partially owned by higher educational institutions and those termed social enterprises contribute better to employment creation than those without the full control of university’s management. Spin offs do contribute insignificantly to revenue generation.

A Modified Version of AlQuAnS: An Arabic Language Question Answering System

Abstract: The challenges of the Arabic language and the lack of resources have made it difficult to provide Arabic Question Answering (QA) systems with high accuracy. These challenges motivated us to propose AlQuAnS-an Arabic Language Question Answering System that gives promising accuracy results. This paper proposes a modified version of AlQuAnS with a higher accuracy. The proposed system enhances the accuracy of the question classification, semantic interpreter and answer extraction modules. The provided performance evaluation study shows that our modified system outperforms other existing Arabic QA systems, especially with the newly introduced answer extraction module.

Definition of Experience Feedback Sheet for Eco-design.

Abstract: In this paper, we propose a Knowledge to use experience feedback techniques in order to keep track of ecodesign decisions. The integration of eco-design in industries is becoming more and more considered as a necessary condition of Sustainable development. Even sustainable rules become to be defined as norms, but the application of these rules in design still difficult. Firstly, eco-design criteria are extracted from documents in order to help the definition of experience feedback sheets main points. CommonKADS generic models are also used in order to define adequate sheets to reasoning and task types linked to eco-design phases.

A New Idea for Enterprise Resource Management.

Abstract: Nowadays the mobile market, thanks to latest generation smartphones, is still spreading: this is mainly due to increasingly powerful computing tools (microprocessors quad core) and to the used operating systems; Android stands among those with the greatest growth. The fields with a strong growth are those linked to mobile advertising, mobile infotainment and B2C mobile services, within which our proposal takes place. The starting idea of this paper is to show the abilities of the implementation of an integrated platform able to support an organization on its authorization, communication and sharing processes, accessible from mobile devices such as smartphones and tablets belonging to employees or customers of an enterprise.