6,448 research outputs found

    Web site audience segmentation using hybrid alignment techniques

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    We are working on behavioral marketing in the Internet. On one hand we observe the behavior of visitors, and on the other hand we trigger (in real-time) stimulations intended to alter this behavior. Real-time and mass-customization are the two challenges that we have to address. In this paper, we present a hybrid approach for clustering visitor sessions, based on a combination of global and local sequence alignments, such as Needleman-Wunsch and Smith-Waterman. Our goal is to define very simple approaches able to address about 80 % of visitor sessions to be segmented, and which can be easily turned into small pieces of program, to be run in parallel in thousands of web browsers

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Systematic Review on Privacy Categorization

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    In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people's decisions when facing with privacy and security trade-offs, the pressing and time consuming disincentives that influence those decisions, and methods to mitigate them. This work aims to present a systematic review of the literature on privacy categorization, which has been defined in terms of profile, profiling, segmentation, clustering and personae. Privacy categorization involves the possibility to classify users according to specific prerequisites, such as their ability to manage privacy issues, or in terms of which type of and how many personal information they decide or do not decide to disclose. Privacy categorization has been defined and used for different purposes. The systematic review focuses on three main research questions that investigate the study contexts, i.e. the motivations and research questions, that propose privacy categorisations; the methodologies and results of privacy categorisations; the evolution of privacy categorisations over time. Ultimately it tries to provide an answer whether privacy categorization as a research attempt is still meaningful and may have a future

    A free customizable tool for easy integration of microfluidics and smartphones

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    The integration of smartphones and microfluidics is nowadays the best possible route to achieve effective point-of-need testing (PONT), a concept increasingly demanded in the fields of human health, agriculture, food safety, and environmental monitoring. Nevertheless, efforts are still required to integrally seize all the advantages of smartphones, as well as to share the developments in easily adoptable formats. For this purpose, here we present the free platform appuente that was designed for the easy integration of microfluidic chips, smartphones, and the cloud. It includes a mobile app for end users, which provides chip identification and tracking, guidance and control, processing, smart-imaging, result reporting and cloud and Internet of Things (IoT) integration. The platform also includes a web app for PONT developers, to easily customize their mobile apps and manage the data of administered tests. Three application examples were used to validate appuente: a dummy grayscale detector that mimics quantitative colorimetric tests, a root elongation assay for pesticide toxicity assessment, and a lateral flow immunoassay for leptospirosis detection. The platform openly offers fast prototyping of smartphone apps to the wide community of lab-on-a-chip developers, and also serves as a friendly framework for new techniques, IoT integration and further capabilities. Exploiting these advantages will certainly help to enlarge the use of PONT with real-time connectivity in the near future.Fil: Schaumburg, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Vidocevich, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Gerlero, Gabriel Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Pujato, Nazarena. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Macagno, Joana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Kler, Pablo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Berli, Claudio Luis Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

    Internet web marketing challenges of South African SMEs

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    This research aims to establish Internet web marketing challenges of South African SMEs.  The research design chosen for this research is descriptive research in conjunction with a quantitative approach.  The population includes SMEs in South Africa.  The sample for the study encompasses 500 SME owners who currently manage the SMEs in South Africa. The conducted research indicated that SME owners utilize the internet web for marketing their businesses.  The research results showed that the wed is promising marketing advertising tool for the future.  The results also revealed that older respondents are more successful in stimulating better sales and customer support through their internet marketing communication efforts than younger respondents while younger respondents are more successful in increasing product awareness and overall productivity of their SME than older respondents. Past research has proven that the web will not render traditional media obsolete.  This is because traditional media has advantages that advertisers cannot ignore and the web cannot take away.  This results show that the web is comparable to other marketing media.  It is therefore important that SME owners include the web as part of their communication mix since an integrated approach is needed

    Proceedings of the ACM SIGIR Workshop ''Searching Spontaneous Conversational Speech''

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    Patterns and Pathways: Applying Social Network Analysis to Understand User Behavior in the Tourism Industry Websites

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    The contemporary tourism landscape is undergoing rapid digitization, necessitating a nuanced comprehension of online user behavior to guide data-driven decision-making. This research bridges an existing gap by investigating the tourism website ecosystem through social network analysis. It focuses specifically on inter-website communication patterns based on user navigation. Data mining facilitates the identification of 162 core Iranian tourism websites, which are visualized as an interconnected network with websites as nodes and user transitions as weighted directed edges. By implementing community detection, eight key clusters are discerned, encompassing domains like ticket/tour bookings, accommodations, location services, and cuisine. Further analysis of inter-community relationships reveals website groupings frequently accessed together by users, highlighting complementary services sought during travel planning. The research derives invaluable insights into user preferences and information propagation within the tourism ecosystem. The methodology and findings contribute original perspectives to academia while offering pragmatic strategic recommendations to industry stakeholders like service providers, investors, and policymakers. This pioneering exploration of latent user behavior patterns advances comprehension of the evolving digital tourism landscape in Iran. It contributes pathways toward a sustainable future vision of the ecosystem, guiding stakeholders in targeted decision-making based on empirical evidence derived from social network analysis of websites and consumption patterns. The innovative methodology expands the toolkit for data-driven tourism research within academia
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