217,821 research outputs found

    Approaches to the use of sensor data to improve classroom experience

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    quipping classrooms with inexpensive sensors can enable students and teachers with the opportunity to interact with the classroom in a smart way. In this paper an approach to acquiring contextual data from a classroom environment, using inexpensive sensors, is presented. We present our approach to formalising the usage data. Further we demonstrate how the data was used to model specific room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was than integrated in a room recommendations system, reasoning on the formalised usage data. We also detail on our on-going work to integrating the systems presented in this paper into our Smart University vision

    A Hybrid Web Recommendation System based on the Improved Association Rule Mining Algorithm

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    As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system. In case of collaborative recommen-dation systems, these try to seek out users who share same tastes that of given user as well as recommends the websites according to the liking given user. Whereas the content based recommendation systems tries to recommend web sites similar to those web sites the user has liked. In the recent research we found that the efficient technique based on asso-ciation rule mining algorithm is proposed in order to solve the problem of web page recommendation. Major problem of the same is that the web pages are given equal importance. Here the importance of pages changes according to the fre-quency of visiting the web page as well as amount of time user spends on that page. Also recommendation of newly added web pages or the pages those are not yet visited by users are not included in the recommendation set. To over-come this problem, we have used the web usage log in the adaptive association rule based web mining where the asso-ciation rules were applied to personalization. This algorithm was purely based on the Apriori data mining algorithm in order to generate the association rules. However this method also suffers from some unavoidable drawbacks. In this paper we are presenting and investigating the new approach based on weighted Association Rule Mining Algorithm and text mining. This is improved algorithm which adds semantic knowledge to the results, has more efficiency and hence gives better quality and performances as compared to existing approaches.Comment: 9 pages, 7 figures, 2 table

    Challenges in context-aware mobile language learning: the MASELTOV approach

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    Smartphones, as highly portable networked computing devices with embedded sensors including GPS receivers, are ideal platforms to support context-aware language learning. They can enable learning when the user is en-gaged in everyday activities while out and about, complementing formal language classes. A significant challenge, however, has been the practical implementation of services that can accurately identify and make use of context, particularly location, to offer meaningful language learning recommendations to users. In this paper we review a range of approaches to identifying context to support mobile language learning. We consider how dynamically changing aspects of context may influence the quality of recommendations presented to a user. We introduce the MASELTOV project’s use of context awareness combined with a rules-based recommendation engine to present suitable learning content to recent immigrants in urban areas; a group that may benefit from contextual support and can use the city as a learning environment

    The Power of Point of Sale Improving Growth, Profit, and Customer Service in a Retail Business

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    For many small businesses, creating a captivating retail experience is the key to success, and finding the right technologies to enable that experience is crucial for sustaining a competitive advantage. This project is a case study designed to evaluate and select a Point of Sale (POS) system and Inventory Management (IM) system for a small business based upon its specific industry needs. The project creates a three step framework leading up to the real world implementation of these systems and uses the Rhode Island based company - Wildwood Inc. - as the subject of the study. Wildwood Inc. is a garden center and nursery that uses manual processes for both its checkout and inventory management practices, but due to its growth is experiencing difficulties in serving its customers effectively. The project looks at specific challenges facing Wildwood and creates a roadmap for POS and IM implementation that can be generalized for businesses looking to upgrade their systems. The framework for the implementation includes (1) initial research and current process analysis, (2) new system evaluation and process comparison, and (3) a final recommendation for management. The project explores the necessary capabilities of POS and IM systems within the retail agriculture industry; creates a comparison matrix of potential product offerings based upon hardware components, software features, technical support, and price points; and develops a final recommendation for Wildwood considering its specific needs. Upon completion, Wildwood will have the information necessary to purchase a computerized system that can: (1) Maintain a database of all inventory, including plant characteristics, units in stock, price, supplier, and SKU number, (2) facilitate a more efficient checkout method that eliminates handwritten receipts of purchases and digitally records all sales within the system, expedites the checkout process for both customers and employees, and 4 communicates with the IM system to allow for real-time inventory updates upon completion of POS transactions, and (3) runs a variety of reports on the collected data so that management has greater accuracy and success when making business decisions
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