Metodi e strumenti di business intelligence per i processi di ciclo attivo: un caso di studio in un?azienda di servizi

Relazione tecnica e funzionale, con rimandi teorici disciplinari, riguardo la realizzazione di un sistema informatico su piattaforma Microsoft per l'organizzazione e la fruizione delle informazioni di Ciclo attivo in un'azienda di servizi di grandi dimensioni.

Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

Linguistic linked data for sentiment analysis

In this paper we describe the specification of amodel for the semantically interoperable representation of language resources for sentiment analysis. The model integrates "lemon", an RDF-based model for the specification of ontology-lexica (Buitelaar et al. 2009), which is used increasinglyfor the representation of language resources asLinked Data, with Marl, an RDF-based model for the representation of sentiment annotations (West-erski et al., 2011; Sánchez-Rada et al., 2013)

DAEDALUS at SemEval-2014 Task 9: Comparing approaches for sentiment analysis in twitter

This paper describes our participation at SemEval- 2014 sentiment analysis task, in both contextual and message polarity classification. Our idea was to com- pare two different techniques for sentiment analysis. First, a machine learning classifier specifically built for the task using the provided training corpus. On the other hand, a lexicon-based approach using natural language processing techniques, developed for a ge- neric sentiment analysis task with no adaptation to the provided training corpus. Results, though far from the best runs, prove that the generic model is more robust as it achieves a more balanced evaluation for message polarity along the different test sets.

EUROSENTIMENT: Linked Data Sentiment Analysis

Sentiment and Emotion Analysis strongly depend on quality language resources, especially sentiment dictionaries. These resources are usually scattered, heterogeneous and limited to specific domains of appli- cation by simple algorithms. The EUROSENTIMENT project addresses these issues by 1) developing a common language resource representation model for sentiment analysis, and APIs for sentiment analysis services based on established Linked Data formats (lemon, Marl, NIF and ONYX) 2) by creating a Language Resource Pool (a.k.a. LRP) that makes avail- able to the community existing scattered language resources and services for sentiment analysis in an interoperable way. In this paper we describe the available language resources and services in the LRP and some sam- ple applications that can be developed on top of the EUROSENTIMENT LRP.

Evaluating EmotiBlog robustness for sentiment analysis tasks

EmotiBlog is a corpus labelled with the homonymous annotation schema designed for detecting subjectivity in the new textual genres. Preliminary research demonstrated its relevance as a Machine Learning resource to detect opinionated data. In this paper we compare EmotiBlog with the JRC corpus in order to check the EmotiBlog robustness of annotation. For this research we concentrate on its coarse-grained labels. We carry out a deep ML experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC demonstrating the EmotiBlog validity as a resource for the SA task.

Business systems purpose, analysis

This thesis deals with the problematic of the business systems systemic purpose definition. The definition of the systemic purpose, which is regarded as the utmost expression of the system's purposefulness, is to be achieved by ensuring the participation of all the stakeholders, if possible, who affect or they are affected by the business system's operations. The nature of participation, defined as a process of the stakeholders' perceptual exchanges, is deemed to be problematic in itself due to the influence exerted upon it by organisational power, coercion and false consciousness. The main focus of the thesis then is to make aware and provide the stakeholders with an explicit philosophical pedestal and a set of principles upon which a meta- epistemological framework for the enquiry of the business system's purposeful behaviour is developed. In addition, the thesis focuses on the development of a methodology that can be used by the stakeholders to achieve self-knowledge through the critical and systemic examination of their normative presuppositions, about the business system, at both sociological as well as the psychological levels concurrently and the subsequent development of an organisational intrinsically motivated information system. According to the critical systems philosophy and principles, developed in this thesis, normative presuppositions define the stakeholders' perceptions about the purposeful behaviour of the business system they perceived as having a material, an informational and/or an emacipatory stake (human interest) in. The methodology will provide Information Systems that demonstrably improve coordination of organisational activities by enabling the development and maintenance of a single/multifaceted view of purpose throughout organisations.

Using QFD for e-business planning and analysis in a micro-sized enterprise

Purpose - The purpose of this paper is to show how QFD can be used as part of a structured planning and analysis framework for micro-sized enterprises to build-up their e-business capabilities. Design/methodology/approach - This case study has been produced using a new framework which integrates the balanced scorecard, value chain and quality function deployment techniques into an integrated framework known as the E-Business Planning and Analysis Framework (E-PAF). It has been produced using an action research approach. Findings - A new framework with a supporting case study is provided. This case study has demonstrated that the framework can be applied successfully to micro-sized enterprises (those with less than ten employees) to successfully plan new strategic and technical developments. This will enhance the online service that the company is able to provide. Research limitations/implications - This paper presents a single case study. The technical recommendations are currently being implemented. Originality/value - Such analytical techniques are most commonly associated with large organisations, and are not specifically associated with e-business planning. This paper provides a new framework that will be of general applicability to other similarly sized enterprises that are looking to improve e-business capabilities. © Emerald Group Publishing Limited.

Incorporating sentiment prior knowledge for weakly supervised sentiment analysis

This article presents two novel approaches for incorporating sentiment prior knowledge into the topic model for weakly supervised sentiment analysis where sentiment labels are considered as topics. One is by modifying the Dirichlet prior for topic-word distribution (LDA-DP), the other is by augmenting the model objective function through adding terms that express preferences on expectations of sentiment labels of the lexicon words using generalized expectation criteria (LDA-GE). We conducted extensive experiments on English movie review data and multi-domain sentiment dataset as well as Chinese product reviews about mobile phones, digital cameras, MP3 players, and monitors. The results show that while both LDA-DP and LDAGE perform comparably to existing weakly supervised sentiment classification algorithms, they are much simpler and computationally efficient, rendering themmore suitable for online and real-time sentiment classification on the Web. We observed that LDA-GE is more effective than LDA-DP, suggesting that it should be preferred when considering employing the topic model for sentiment analysis. Moreover, both models are able to extract highly domain-salient polarity words from text.

E-business planning and analysis framework

This chapter reports on a framework that has been successfully used to analyze the e-business capabilities of an organization with a view to developing their e-capability maturity levels. This should be the first stage of any systems development project. The framework has been used widely within start-up companies and well-established companies both large and small; it has been deployed in the service and manufacturing sectors. It has been applied by practitioners and consultants to help improve e-business capability levels, and by academics for teaching and research purposes at graduate and undergraduate levels. This chapter will provide an account of the unique e-business planning and analysis framework (E-PAF) and demonstrate how it works via an abridged version of a case study (selected from hundreds that have been produced). This will include a brief account of the three techniques that are integrated to form the analysis framework: quality function deployment (QFD) (Akao, 1972), the balanced scorecard (BSC) (Kaplan & Norton, 1992), and value chain analysis (VCA) (Porter, 1985). The case study extract is based on an online community and dating agency service identified as VirtualCom which has been produced through a consulting assignment with the founding directors of that company and has not been published previously. It has been chosen because it gives a concise, comprehensive example from an industry that is relatively easy to relate to.

Learning higher-level features with convolutional restricted Boltzmann machines for sentiment analysis

In recent years, learning word vector representations has attracted much interest in Natural Language Processing. Word representations or embeddings learned using unsupervised methods help addressing the problem of traditional bag-of-word approaches which fail to capture contextual semantics. In this paper we go beyond the vector representations at the word level and propose a novel framework that learns higher-level feature representations of n-grams, phrases and sentences using a deep neural network built from stacked Convolutional Restricted Boltzmann Machines (CRBMs). These representations have been shown to map syntactically and semantically related n-grams to closeby locations in the hidden feature space. We have experimented to additionally incorporate these higher-level features into supervised classifier training for two sentiment analysis tasks: subjectivity classification and sentiment classification. Our results have demonstrated the success of our proposed framework with 4% improvement in accuracy observed for subjectivity classification and improved the results achieved for sentiment classification over models trained without our higher level features.

Systemological Bases of Business Intelligence

Sustainable development support, balanced scorecard development and business process modeling are viewed from the position of systemology. Extensional, intentional and potential properties of a system are considered as necessary to satisfy functional requirements of a meta-system. The correspondence between extensional, intentional and potential properties of a system and sustainable, unsustainable, crisis and catastrophic states of a system is determined. The inaccessibility cause of the system mission is uncovered. The correspondence between extensional, intentional and potential properties of a system and balanced scorecard perspectives is showed. The IDEF0 function modeling method is checked against balanced scorecard perspectives. The correspondence between balanced scorecard perspectives and IDEF0 notations is considered.