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|Title:||The SCSE memory project||Authors:||Ong, Han Xiang||Keywords:||Engineering::Computer science and engineering::Information systems::Information storage and retrieval||Issue Date:||2020||Publisher:||Nanyang Technological University||Abstract:||In olden times, photos are often captured by individuals and stored in a physical form. Through this, the individual would be able to preserve their memories so that they could reminisce about the past. With the breakthrough of technology, these photos are then converted into images. Since then, it has been an important asset to every individual in the digital world. As such, numerous systems have been developed and released to the public to allow the individual to better access and manage their images. At the current age, there are various social media platforms that have revolutionized how individuals interact with one another and how it allows them to extract information in a fraction of seconds. For instance, Facebook, Instagram, and Flickr have been the most competent in doing so. However, these social media platforms are often exploited by cybercriminals to obtain digital assets in a form of images and its semantic keywords from an organization. In order to safeguard these digital assets, it is imperative to release applications that are exclusive to the specific organization. This project implements a collective organizational memory system named SCSE Memory that caters to the School of Computer Science and Engineering (SCSE) in Nanyang Technological University (NTU). SCSE Memory facilitates the management of digital assets in a form of images and its semantic keywords. This is accomplished by building the SCSE Memory system on top of previous SnapMemory and MyLife applications. The SCSE Memory system is divided into 2 components: Annotator and Visualizer. The SCSE Memory Annotator is a web application that encourages the SCSE community to view and manage the digital assets. As an alternative, SnapMemory is an Android application that will be used for individuals to upload and annotate their media with semantic keywords on the go. On the other hand, SCSE Memory Visualizer is built upon the MyLife application that utilizes the Autobiographical Memory Adaptive Resonance Theory (AM-ART) network to mimic the autobiographical memory of a human brain. As such, it is able to handle imperfect queries, which most existing applications cannot handle. In addition, it also supports vigilance and wander functions that may help individual to retrieve their memories that may seem to be a random dataset but in fact are contextually related. All in all, it enables individuals to retrieve their memories based on the provided cues. The memory playback will be then be displayed into slideshows with movie-like effects to enhance the user’s experience. With the enhancements and new functions implemented, a collective organizational memory system had been put in place to cater to the needs of SCSE and its community.||URI:||https://hdl.handle.net/10356/137924||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Student Reports (FYP/IA/PA/PI)|
Updated on Dec 7, 2022
Updated on Dec 7, 2022
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