Flexible context aware interface for ambient assisted living

McNaull, James; Augusto, Juan Carlos; Mulvenna, Maurice; McCullagh, Paul

doi:10.1186/2192-1962-4-1

Cited by 37 publications

(17 citation statements)

References 33 publications

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“…The concept of the filter bubble is used to target a specific group of people to spread the specific misinformation. As per Kumar & Geethakumari (2014) cognitive psychology plays an important role in the spread of misinformation.…”

Section: Introductionmentioning

confidence: 99%

Stance detection with BERT embeddings for credibility analysis of information on social media

Karande

Walambe

Benjamin

et al. 2021

PeerJ Computer Science

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The evolution of electronic media is a mixed blessing. Due to the easy access, low cost, and faster reach of the information, people search out and devour news from online social networks. In contrast, the increasing acceptance of social media reporting leads to the spread of fake news. This is a minacious problem that causes disputes and endangers the societal stability and harmony. Fake news spread has gained attention from researchers due to its vicious nature. proliferation of misinformation in all media, from the internet to cable news, paid advertising and local news outlets, has made it essential for people to identify the misinformation and sort through the facts. Researchers are trying to analyze the credibility of information and curtail false information on such platforms. Credibility is the believability of the piece of information at hand. Analyzing the credibility of fake news is challenging due to the intent of its creation and the polychromatic nature of the news. In this work, we propose a model for detecting fake news. Our method investigates the content of the news at the early stage i.e., when the news is published but is yet to be disseminated through social media. Our work interprets the content with automatic feature extraction and the relevance of the text pieces. In summary, we introduce stance as one of the features along with the content of the article and employ the pre-trained contextualized word embeddings BERT to obtain the state-of-art results for fake news detection. The experiment conducted on the real-world dataset indicates that our model outperforms the previous work and enables fake news detection with an accuracy of 95.32%.

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Section: Introductionmentioning

confidence: 99%

Stance detection with BERT embeddings for credibility analysis of information on social media

Karande

Walambe

Benjamin

et al. 2021

PeerJ Computer Science

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“…A framework for context-aware adaptivity of user interfaces for the elderly (AALFI) has been recently proposed [10]. It aims to enable context dependent adaptation of UI applications for supporting elderly users during both days and nights.…”

Section: Related Workmentioning

confidence: 99%

Adaptive multimodal web user interfaces for smart work environments

Ghiani

Manca

Paternò

et al. 2015

AIS

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This paper presents a solution for supporting adaptive user interfaces in work environments that require operators to move about in dynamic contexts for manipulating various physical objects. The solution architecture is built upon the use of logical languages for interactive applications integrated with context aware and adaptive features. The proposed architecture is able to adapt to specific aspects of the context during run-time by communicating with a context server and applying the specified adaptation rules. In order to show the possibilities of the proposed solution, we report on its application in the development of an adaptive user interface for a warehouse picking system, and discuss the results of the associated tests.

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“…Data privacy protection is still a major concern in smart environments, although there have been efforts to protect personal information of the users by using mobile agents [ 22 ] and deploying security framework [ 23 ] and context-based solutions (e.g., context-sensitive services [ 12 ] and context-aware interface [ 24 ]). Context is often referred to as information used to identify activities or events that have occurred in the smart environment.…”

Section: Background and Related Workmentioning

confidence: 99%

Preserving Differential Privacy for Similarity Measurement in Smart Environments

Wong

2014

The Scientific World Journal

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Advances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people's life and living styles. However, collecting and storing user's data in the smart environments pose severe privacy concerns because these data may contain sensitive information about the subject. Hence, privacy protection is now an emerging issue that we need to consider especially when data sharing is essential for analysis purpose. In this paper, we consider the case where two agents in the smart environment want to measure the similarity of their collected or stored data. We use similarity coefficient function (scriptFscriptSscriptC) as the measurement metric for the comparison with differential privacy model. Unlike the existing solutions, our protocol can facilitate more than one request to compute scriptFscriptSscriptC without modifying the protocol. Our solution ensures privacy protection for both the inputs and the computed scriptFscriptSscriptC results.

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Flexible context aware interface for ambient assisted living

Cited by 37 publications

References 33 publications

Stance detection with BERT embeddings for credibility analysis of information on social media

Stance detection with BERT embeddings for credibility analysis of information on social media

Adaptive multimodal web user interfaces for smart work environments

Preserving Differential Privacy for Similarity Measurement in Smart Environments

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