Comparing Regime-Switching Models In Time Series: Logistic Mixtures vs. Markov Switching

The purpose of this thesis is to review several related regime-switching time series models. Specifically, we use simulated data to compare models where the unobserved state vector follows a Markov process against an independent logistic mixture process. We apply these techniques to crude oil and heating oil futures prices using several explanatory variables to estimate the unobserved regimes. We find that crude oil is characterized by regime switching, where prices alternate between a high volatility state with low returns and significant mean reversion and a low volatility state with positive returns and some trending. The spread between one-month and three-month futures prices is an important determinant in the dynamics of crude oil prices

The Degradome database: mammalian proteases and diseases of proteolysis

The degradome is defined as the complete set of proteases present in an organism. The recent availability of whole genomic sequences from multiple organisms has led us to predict the contents of the degradomes of several mammalian species. To ensure the fidelity of these predictions, our methods have included manual curation of individual sequences and, when necessary, direct cloning and sequencing experiments. The results of these studies in human, chimpanzee, mouse and rat have been incorporated into the Degradome database, which can be accessed through a web interface at http://degradome.uniovi.es. The annotations about each individual protease can be retrieved by browsing catalytic classes and families or by searching specific terms. This web site also provides detailed information about genetic diseases of proteolysis, a growing field of great importance for multiple users. Finally, the user can find additional information about protease structures, protease inhibitors, ancillary domains of proteases and differences between mammalian degradomes

Webometrics benefitting from web mining? An investigation of methods and applications of two research fields

Webometrics and web mining are two fields where research is focused on quantitative analyses of the web. This literature review outlines definitions of the fields, and then focuses on their methods and applications. It also discusses the potential of closer contact and collaboration between them. A key difference between the fields is that webometrics has focused on exploratory studies, whereas web mining has been dominated by studies focusing on development of methods and algorithms. Differences in type of data can also be seen, with webometrics more focused on analyses of the structure of the web and web mining more focused on web content and usage, even though both fields have been embracing the possibilities of user generated content. It is concluded that research problems where big data is needed can benefit from collaboration between webometricians, with their tradition of exploratory studies, and web miners, with their tradition of developing methods and algorithms

Social Customer Relationship Management: A Case Study

Social Customer Relationships Management (CRM) is a current business trend providing new channels of two-way communication with customers through social media sites, such as Facebook, Twitter etc. Social CRM enables companies to interact in an easy and contemporary way directly with customers as well as to track customer interactions and their social influence. In this paper we examine the importance of CRM, e-CRM and Social CRM for businesses. We provide perspectives on objectives and types of CRM, the working cycle of CRM, the stages of a CRM Strategy and technology tools that are used in CRM. Social CRM is in particularly analyzed, since this new trend requires active engagement by customers and other stakeholders. The engagement process is essential to successful Social CRM and to successful social business practices. Finally, we describe experiences from three family businesses that introduced Social CRM as a result of a project carried out as an assignment in the ‘Social Media Networking’ module of the MSc course in ‘Web Intelligence’ at the Department of Informatics of Alexander Technological Educational Institute of Thessaloniki. The assignment of the groups was to create a Social CRM Strategy in collaboration with a company. This study is a follow-up of the outcome of the projects carried out in the autumn semester 2014 and 2015. The results show that all three companies consider that Social CRM is an excellent tool for obtaining real time valuable data about customers and a cheap way to reach them