Intelligent methods for information access in context: The role of topic descriptors and discriminators

Successful access to information sources on the Web depends on effective methods for identifying the needs of a user and making relevant information resources available when needed. This paper formulates a theoretical framework for the study of context-drivenWeb search and proposes new methods for learning query terms based on the user task. These methods use an incrementally-retrieved, topic-dependent selection of Web documents for term-weight reinforcement reflecting the aptness of the terms in describing and discriminating the topic of the user context. Based on this framework, we propose an incremental search algorithm for information retrieval agents that has the potential to improve significantly over the traditional IR techniques. The new algorithm learns new descriptors by searching for terms that tend to occur often in relevant documents, and learns good discriminators by identifying terms that tend to occur only in the context of the given topic. We discuss the technical challenges posed by this new framework, outline our agent system architecture, and present an evaluation of the proposed techniques.Red de Universidades con Carreras en Informática (RedUNCI

OptiqueVQS: A visual query system over ontologies for industry

An important application of semantic technologies in industry has been the formalisation of information models using OWL 2 ontologies and the use of RDF for storing and exchanging application data. Moreover, legacy data can be virtualised as RDF using ontologies following the ontology-based data access (OBDA) approach. In all these applications, it is important to provide domain experts with query formulation tools for expressing their information needs in terms of queries over ontologies. In this work, we present such a tool, OptiqueVQS, which is designed based on our experience with OBDA applications in Statoil and Siemens and on best HCI practices for interdisciplinary engineering environments. OptiqueVQS implements a number of unique techniques distinguishing it from analogous query formulation systems. In particular, it exploits ontology projection techniques to enable graph-based navigation over an ontology during query construction. Secondly, while OptiqueVQS is primarily ontology driven, it exploits sampled data to enhance selection of data values for some data attributes. Finally, OptiqueVQS is built on well-grounded requirements, design rationale, and quality attributes. We evaluated OptiqueVQS with both domain experts and casual users and qualitatively compared our system against prominent visual systems for ontology-driven query formulation and exploration of semantic data. OptiqueVQS is available online and can be downloaded together with an example OBDA scenario

Implementing Web 2.0 in secondary schools: impacts, barriers and issues

One of the reports from the Web 2.0 technologies for learning at KS3 and KS4 project. This report explored Impact of Web 2.0 technologies on learning and teaching and drew upon evidence from multiple sources: field studies of 27 schools across the country; guided surveys of 2,600 school students; 100 interviews and 206 online surveys conducted with managers, teachers and technical staff in these schools; online surveys of the views of 96 parents; interviews held with 18 individual innovators in the field of Web 2.0 in education; and interviews with nine regional managers responsible for implementation of ICT at national level

INDIGO: a generalized model and framework for performance prediction of data dissemination

According to recent studies, an enormous rise in location-based mobile services is expected in future. People are interested in getting and acting on the localized information retrieved from their vicinity like local events, shopping offers, local food, etc. These studies also suggested that local businesses intend to maximize the reach of their localized offers/advertisements by pushing them to the maxi- mum number of interested people. The scope of such localized services can be augmented by leveraging the capabilities of smartphones through the dissemination of such information to other interested people. To enable local businesses (or publishers) of localized services to take in- formed decision and assess the performance of their dissemination-based localized services in advance, we need to predict the performance of data dissemination in complex real-world scenarios. Some of the questions relevant to publishers could be the maximum time required to disseminate information, best relays to maximize information dissemination etc. This thesis addresses these questions and provides a solution called INDIGO that enables the prediction of data dissemination performance based on the availability of physical and social proximity information among people by collectively considering different real-world aspects of data dissemination process. INDIGO empowers publishers to assess the performance of their localized dissemination based services in advance both in physical as well as the online social world. It provides a solution called INDIGO–Physical for the cases where physical proximity plays the fundamental role and enables the tighter prediction of data dissemination time and prediction of best relays under real-world mobility, communication and data dissemination strategy aspects. Further, this thesis also contributes in providing the performance prediction of data dissemination in large-scale online social networks where the social proximity is prominent using INDIGO–OSN part of the INDIGO framework under different real-world dissemination aspects like heterogeneous activity of users, type of information that needs to be disseminated, friendship ties and the content of the published online activities. INDIGO is the first work that provides a set of solutions and enables publishers to predict the performance of their localized dissemination based services based on the availability of physical and social proximity information among people and different real-world aspects of data dissemination process in both physical and online social networks. INDIGO outperforms the existing works for physical proximity by providing 5 times tighter upper bound of data dissemination time under real-world data dissemination aspects. Further, for social proximity, INDIGO is able to predict the data dissemination with 90% accuracy and differently, from other works, it also provides the trade-off between high prediction accuracy and privacy by introducing the feature planes from an online social networks

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work

Intelligent methods for information access in context: The role of topic descriptors and discriminators

Successful access to information sources on the Web depends on effective methods for identifying the needs of a user and making relevant information resources available when needed. This paper formulates a theoretical framework for the study of context-drivenWeb search and proposes new methods for learning query terms based on the user task. These methods use an incrementally-retrieved, topic-dependent selection of Web documents for term-weight reinforcement reflecting the aptness of the terms in describing and discriminating the topic of the user context. Based on this framework, we propose an incremental search algorithm for information retrieval agents that has the potential to improve significantly over the traditional IR techniques. The new algorithm learns new descriptors by searching for terms that tend to occur often in relevant documents, and learns good discriminators by identifying terms that tend to occur only in the context of the given topic. We discuss the technical challenges posed by this new framework, outline our agent system architecture, and present an evaluation of the proposed techniques.Red de Universidades con Carreras en Informática (RedUNCI

Workflow repository for providing configurable workflow in ERP

Workflow pada ERP dengan domain fungsi yang besar rentan dengan adanya duplikasi. Membuat workflow repository yang menyimpan berbagai macam workflow dari proses bisnis ERP yang dapat digunakan untuk menyusun workflow baru sesuai kebutuhan tenant baru Metode yang diusulkan: Metode yang diusulkan terdiri dari 2 tahapan, preprocessing dan processing. Tahap preprocessing bertujuan untuk mencari common dan sub variant dari existing workflow variant. Workflow variant yang disimpan oleh pengguna adalah Procure to Pay workflow. Variasi tersebut diseleksi berdasarkan kemiripannya dengan similarity filtering, kemudian dimerge untuk mencari common dan sub variantnya. Common dan sub variant disimpan menggunakan metadata yang dipetakan pada basis data relasional. Deteksi common dan sub variant workflow mencapai tingkat akurasi sebesar 92%. Ccommon workflow terdiri dari 3-common dari 8-variant workflow. Common workflow tersebut memiliki tingkat kompleksitas lebih rendah 10% dari model sebelumnya. Tahapan processing adalah tahapan penyediaan configurable workflow. Pengguna memasukan query model untuk mencari workflow yang diinginkan. Dengan menggunakan metode similarity filtering, didapatkan common dan/atau sub variant yang memungkinkan. Pengguna dapat menggunakan common workflow melalui workflow designer untuk melakukan rekomposisi ulang. Penyediaan configurable workflow oleh ERP mencapai tingkat 100% dimana apapun yang diinginkan pengguna dapat disediakaan workflownya oleh ERP, ataupun sebagai dasar membentuk workflow yang lain. Berdasarkan hasil percobaan, tempat penyimpanan workflow dapat dibangun dengan arsitektur yang diajukan dan mampu menyimpan dan menyediakan workflow. Tempat penyimpanan ERP mampu mendeteksi workflow yang bersifat common dan sub variant. Tempat penyimpanan ERP mampu menyediakan configurable workflow, dimana pengguna dapat memanfaatkan common dan sub variant workflow untuk menjadi dasar mengkomposisi workflow yang lain. =================================================================================================== Workflow in ERP which covered big domain faced duplication issues. Scope of this research was developing workflow from business process ERP which could be used for required workflow as user needs. Proposed approach consisted of 2 stages preprocessing and processing. Preprocessing stages aimed for finding common and variant of sub workflow based on existing workflow variant. The workflow variants that were stored by user were procured to pay workflow. The workflows was filtered by similarity filtering method then merged for identifying the common and variant of sub workflow. The common and sub variant workflow were stored using metadata that mapped into relational database. The common and variant of sub workflow detection achieved 92% accuracy. The common workflow consisted of 3- the common workflow from 8-variant workflow. The common workflow has 10% lesser complexity than its predecessor. Processing was providing configurable workflow. User inputted query model to find required workflow. Utilizing similarity filtering, possible the common and variant of sub workflow was collected. User used the common workflow through workflow designer to recompose. Providing configurable workflow ERP achieved 100%, where any user need would be provided by ERP, as workflow or as based template for creating other. Based on evaluation, repository was built based on proposed architecture and was able to store or provide workflow. Repository detected workflow whether common or variant of sub workflow. Repository ERP was able to provide configurable ERP, where user utilized common and variant of sub workflow as based for creating one of their need

SEGURANÇA EM INFRAESTRUTURA PARA INTERNET DAS COISAS

O conceito de Internet das coisas (Internet of Things - IoT) pressupõe que objetos comuns possam estar interligados à Internet, de modo a dotá-los da inteligência necessária para interagir e, de algum modo, auxiliar a vida das pessoas por meio da coleta de dados físicos, processamento e promoção de respostas através de atuadores eletromecânicos. Além do desenvolvimento de tecnologias há de se efetuar a pesquisa e o tratamento dos aspectos de segurança aplicáveis em infraestrutura para Internet das coisas. Dessa forma, este artigo visa primeiro repassar os conceitos teóricos básicos sobre os elementos que compõe a infraestrutura para Internet das Coisas, com destaque para rede de sensores sem fio, middleware e computação em nuvem. Em seguida o trabalho faz um levantamento e discute os desafios e soluções adequadas para a segurança em infraestrutura para Internet das Coisas, em específico a necessidade de manutenção da privacidade dos usuários como também a busca pela interoperabilidade entre os diversos dispositivos inteligentes. Ao final o estudo realiza uma comparação de algumas implementações em infraestrutura para Internet das Coisas em termos de atendimento aos requisitos de segurança da informação: confidencialidade, integridade, disponibilidade, autenticação, controle de acesso e não repúdio e registra os desafios e trabalhos futuros na área

Simulating Light-Weight Personalised Recommender Systems in Learning Networks: A Case for Pedagogy-Oriented and Rating-Based Hybrid Recommendation Strategies

Recommender systems for e-learning demand specific pedagogy-oriented and hybrid recommendation strategies. Current systems are often based on time-consuming, top down information provisioning combined with intensive data-mining collaborative filtering approaches. However, such systems do not seem appropriate for Learning Networks where distributed information can often not be identified beforehand. Providing sound way-finding support for lifelong learners in Learning Networks requires dedicated personalised recommender systems (PRS), that offer the learners customised advise on which learning actions or programs to study next. Such systems should also be practically feasible and be developed with minimized effort. Currently, such so called light-weight PRS systems are scarcely available. This study shows that simulation studies can support the analysis and optimisation of PRS requirements prior to starting the costly process of their development, and practical implementation (including testing and revision) during field experiments in real-life learning situations. This simulation study confirms that providing recommendations leads towards more effective, more satisfied, and faster goal achievement. Furthermore, this study reveals that a light-weight hybrid PRS-system based on ratings is a good alternative for an ontology-based system, in particular for low-level goal achievement. Finally, it is found that rating-based light-weight hybrid PRS-systems enable more effective, more satisfied, and faster goal attainment than peer-based light-weight hybrid PRS-systems (incorporating collaborative techniques without rating).Recommendation Strategy; Simulation Study; Way-Finding; Collaborative Filtering; Rating