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One of the biggest challenges in Big Data is to exploit value from large volumes of variable and changing data. For this, one must focus on analyzing the data in these Big Data sources and classify the data items according to a domain model (e.g. an ontology). To automatically classify unstructured text documents according to an ontology, a hierarchical multi-label classification process called Semantic...
The explosive growth of social networks has led to prolific availability in customer tastes and preferences. This data can be exploited to serve the customers better and offer them the advertisements they would be delighted to see. To provide relevant advertisements to consumers, one has to consider the location of the consumer as well. The consumers will be highly contented if the offers shown to...
The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks. This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data. This architecture...
Nowadays, cities are the common choice for living, representing a complex system where governments need to perform adequately, despite current restrictions, in order to satisfy the needs of the citizens and overcome economic, social and environmental sustainability challenges. The Smart City term emerges to conceptualize the need to understand citizens, namely their services demand and their relevance...
Collaboration among SMEs is playing an increasingly important role in modern business and industry, in order to gather complementary resources and make alliance. According to agglomeration economy theory, several features play crucial rules in matching collaboration among SMEs. In this paper, an effective method of identifying and recommending potential partner relationship is proposed. In the proposed...
In this paper we address the challenge of applying process mining to discover models of human behaviour from sensor data. This challenge is caused by a gap between sensor data and the event logs that are used as input for process mining techniques, so we provide a transformation approach to bridge this gap. As a result, besides the automatic discovery of process models, the transformed sensor data...
This paper presents a new method for automatically extracting smartphone users' contextual behaviors from the digital traces collected during their interactions with their devices. Our goal is in particular to understand the impact of users' context (e.g., location, time, environment, etc.) on the applications they run on their smartphones. We propose a methodology to analyze digital traces and to...
Incorporating user interests evolution over time is a crucial problem in user profiling. We particularly focus on social profiling process that uses information shared on user social network to extract his/her interests. In this work, we apply our existing time-aware social profiling method on Twitter. The aim of this study is to measure the effectiveness of our approach on this kind of social network...
Stream-based data processing systems, such as Complex Event Processing or data stream mining systems, may be composed of several components which may be implemented in various programming languages. In distributed scenarios, computer networks typically represent important bottlenecks. However, the performance of data exchange in local contexts may be as important as the performance of data exchange...
Pointing behavior in childhood is typical developmental sign having strong correlation to his or her language development. This paper focuses on the pointing behavior accompanied by utterance during picture book reading. With this respect, we make use of picture books' review data amounting to approximately 320 thousand, and analyze the reviews reflecting the pointing behavior with children's utterance...
Process Mining aims to extract information from event logs to highlight the underlying business processes. It is useful in situations where there is no detailed and complete knowledge of how an overall system works, such as in a hospital where most processes are complex and ad-hoc. Many Process Mining discovery techniques have been proposed so far, but many challenges are still to be faced. Implicit...
This paper introduces a novel approach for document re-ranking in information retrieval based on topic-comment structure of texts. While most information retrieval models make the assumption that relevant documents are about the query and that aboutness can be captured considering bags of words only, we rather consider a more sophisticated analysis of discourse to capture document relevance by distinguishing...
The use of Computer-Assisted Audit Tools and Techniques can promote the efficacy and the efficiency of auditors' work in attendance control. This control is similar in almost all companies and data extracted from Human Resourses' software is easily accessed and is not complex. After data validation, the procedures that are recommended in this paper can be adapted to any company. Therefore, is our...
With the advance of mobile applications market, there is an increasing concern about the challenges when developing products that meet the many types of users and to harmonize each product with the various usage environments, thus, providing a good user experience. This situation leads to the need to develop a framework that makes applications become aware of the context and provides a self-learning...
Users context is exploited by an increased number of applications, especially mobile ones, in order to provide their clients with context-oriented services. With our work we try to extend the usage context to laptop and desktop applications and environments. This paper aims analyzing user behavior on three different habitats: at work, at school and at home. The main purpose of this paper is to find...
Internet traffic classification is a relevant and mature research field, anyway of growing importance and with still open technical challenges, also due to the pervasive presence of Internet-connected devices into everyday life. We claim the need for innovative traffic classification solutions capable of being lightweight, of adopting a domain-based approach, of not only concentrating on application-...
Nowadays, wireless communication technologies have high influence on our daily lives. The vehicular ad hoc networks (VANETs) is now evolving quickly and attract attention from road operators, car manufacturers and governments. We unveil a fine traffic flow optimization method with VANETs. On the macroscopic level, our model identifies road segment profiles. On the microscopic level, vehicles send...
Aspect Mining is a research domain that tries to identify occurrences of crosscutting concerns in software systems that were developed without using the aspect oriented paradigm. A top-down approach to aspect mining first manually analyzes the pattern(s) used for implementing crosscutting concerns and then tries to automatically identify them in legacy software systems. In this paper we analyze three...
eGovernment in the new context of smart cities aims at improving the participation model of citizens that are no longer mere consumers of services designed and offered by public bodies. The availability of (open) data from the PA and third party organizations, which can be made public and widely accessible, introduces a significant paradigm shift from citizen-centric to citizen-driven eGovernment...
This paper introduces an empirical investigation which directly addresses and explores gender prediction capacity from digitised handwriting data from several different perspectives - such as feature type (static/dynamic) and content (fixed/variable) types - in order to provide extensive experimental evidence and analysis to guide the development of a better understanding of the opportunities for...
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