DCSOFT 2014 Abstracts

Short Papers
Short Papers
Paper Nr: 1
Title:

“No More Spray and Pray Audience Targeting in Mobile World” - IAB based Classification Approach for Mobile App Audience Measurement
Authors:

Kajanan Sangaralingam
Abstract: Mobile app market is overwhelmed with millions of apps. While this has resulted in a burgeoning mobile app market, mobile app constituents face numerous hurdles due to lack of knowledge of their intended audience. However the audience measurement of mobile apps is challenging compared to other media segments (such as print, radio, TV and web). Since the popularity of apps is highly transient the traditional panel based measurements become inappropriate. As the quantity of apps are growing in leaps and bounds on a daily basis, the challenge of measuring the target audience is intensified. Further, due to the volatile and transient nature of mobile app popularity, panel based approaches will not work for mobile apps. Therefore, there is an urgent need to estimate the app audience using a non-panel based reliable technique. Thus motivated, it is proposed a classification based text mining approach to measure mobile app audience. Proposed dynamic approach can be used to estimate the audience of existing 1.5 million apps as well as the incoming new apps. Implications for research and practice are discussed. In addition, future research directions also have been discussed.
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Paper Nr: 2
Title:

A Model-Driven Approach to Create and Maintain an Executable Transferal Management Platform
Authors:

Emanuele Laurenzi
Abstract: My work falls within the eHealth application domain and it is embedded into the just started research project Patient Radar. The Patient Radar project wants to facilitate intersectoral collaboration within the inpatient sector, also called “transferal management”, i.e. between acute hospitals and rehabilitation clinics in Switzerland. My research aims at supporting and optimizing such a collaboration by setting up a framework which adopts a model-driven approach to enable the creation and maintenance of a transferal management platform. The model-driven approach makes the platform highly configurable to accommodate new clinical pathways and be easily extendable to include additional functions to meet future needs. All domain-specific aspects are described declaratively in application models. Hence, domain experts will be able to create/use/manage application models with no required programming skills. To provide an executable platform, models are first specified in the formal semantics description logics and then their elements are mapped to corresponding elements in an application framework. In this way, we will ensure that executable code can be derived from all application models. Additionally, the transferal management platform includes reference models from which domain experts can easily create and adapt application models.
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