Developing a user-centric event management system

This thesis describes the development of a software requirements specification for a user-centric event management system. The system is set to satisfy three goals: adding value for the event attendees, adding value for the event organizer, and reducing the costs of arranging and running an event. The requirements are identified by researching the prescriptive traits of event business and the current state of the case company and its environment. First the professional and human needs for events are scrutinized. Second, some recent reports about the current trends in the event business are reviewed. Then the event life cycle is presented using the model of new service development, and online promotion of events and especially word-of-mouth marketing receive special attention. Events are also regarded from the perspective of social networks and social media. The case company’s current state and its competitors are reviewed to formulate the needs which the system should fulfil. Then the currently available solutions for social media oriented event management are reviewed. The result is a set of functional and non-functional requirements. The functional requirements are categorized into social media, social networking, event personalization, event management, and system administration features. The specified features and non-functional requirements satisfy the three goals set for the system.

Apolipoprotein E and Recovery from Traumatic Brain Injury

The outcome from traumatic brain injury (TBI) is variable and only partly explained by known prognostic factors. This is especially true for predicting long-term outcome. Genetic factors may influence the brain`s susceptibility to injury or capacity for repair and regeneration. To examine the association of apolipoproteinE (apoE) genotype with long-term outcome, hippocampal volumes and general brain atrophy, we determined the apoE genotype from 61 TBI patients who had been injured over on average 31 years earlier. The long-term outcome was evaluated with repeated neuropsychological testing and by applying various measures of everyday functioning and quality of life. Magnetic resonance imaging (MRI) based volumetric analyses of the hippocampus and lateral ventricles were performed. In the prospective study, the purpose was to examine the association between apoE genotype and visibility of traumatic brain lesions during the first year after TBI and the ability of apoE genotype, the Glasgow Coma Score (GCS), MRI findings and duration of posttraumatic amnesia (PTA) to predict the one-year outcome. Thirty-three patients with TBI were studied and the outcome was evaluated with the Head Injury Symptom Checklist (HISC) and the Glasgow Outcome Scale extended version (GOS-E) scores one year after the injury. MRI and apoE genotyping were carried out. After three decades, neither hippocampal nor lateral ventricle volumes differed significantly in those patients with the apoE ε4 allele vs those without this allele, but the TBI patients with the apoE ε4 allele showed significantly poorer general cognitive level than those without this allele. This decline was wholly accounted for by a subgroup of patients who had developed incident or clinical dementia. In the prospective study the apoE genotype was not associated with visible MRI changes or outcome. The duration of PTA and acute MRI were the best predictors of one-year outcome in TBI. A portion of the TBI patients with the apoE ε4 allele seem to be at risk of long-term cognitive decline. This association may involve mechanisms other than those responsible for the development of brain atrophy. The early MRI and PTA have an important role in assessing the injury severity and prognosis.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

Mobile marketing process of an international event – Case: Falun2015 FIS Nordic World Ski Championships

Any other technology has never affected daily life at this level and witnessed as speedy adaptation as the mobile phone. At the same time, mobile media has developed to be a serious marketing tool for all kinds of businesses, and the industry has grown explosively in recent years. The objective of this thesis is to inspect the mobile marketing process of an international event. This thesis is a qualitative case study. The chosen case for this thesis is the mobile marketing process of Falun2015 FIS Nordic World Ski Championships due to researcher’s interest on the topic and contacts to the people around the event. The empirical findings were acquired by conducting two interviews with three experts from the case organisation and its partner organisation. The interviews were performed as semi-structured interviews utilising the themes arising from the chosen theoretical framework. The framework distinguished six phases in the process: (i) campaign initiation, (ii) campaign design, (iii) campaign creation, (iv) permission management, (v) delivery, and (vi) evaluation and analysis. Phases one and five were not examined in this thesis because campaign initiation was not purely seen as part of the campaign implementation, and investigating phase five would have required a very technical viewpoint to the study. In addition to the interviews, some pre-established documents were exploited as a supporting data. The empirical findings of this thesis mainly follow the theoretical framework utilised. However, some modifications to the model could be made mainly related to the order of different phases. In the revised model, the actions are categorised depending on the time they should be conducted, i.e. before, during or after the event. Regardless of the categorisation, the phases can be in different order and overlapping. In addition, the business network was highly emphasised by the empirical findings and is thus added to the modified model. Five managerial recommendations can be concluded from the empirical findings of this thesis: (i) the importance of a business network should be highly valued in a mobile marketing process; (ii) clear goals should be defined for mobile marketing actions in order to make sure that everyone involved is aware them; (iii) interactivity should be perceived as part of a mobile marketing communication; (iv) enough time should be allowed for the development of a mobile marketing process in order to exploit all the potential it can offer; and (v) attention should be paid to measuring and analysing matters that are of relevance