Multimedia Processing by Centralized Public Authentication in Collective Intelligence Media Industries

Abstract

Gathering information on local systems has been one of the greatest challenges in personal computing. The volume of files causes redundancy and noise thus reducing their value. To rank such files is a challenging task. First, we have to solve the access permission problems since we need to access portions of the exclusive database, the local user file systems and the social profile. Second, we have to extract meanings from the files we have obtained. In this thesis, we attempt to solve these problems and demonstrate how web applications might make use of the local user data to perform local media file searches via a centralized local agent. To make better use of the personal files, we introduce PAuth (as known as Public Authentication) to gather, solve and represent a user in the way of pure text.

PAuth takes advantage of both the data we have stored and the tremendously increasing computational power. Personal data is now used in many fields including areas like collective intelligence, social media, profile, smart recommendation, and legacy online searches. It is also now applied to personal media. However the challenging tasks include: 1) sensitive personal files need to be processed and requested made via centralized local agents, and 2) to extract meaning of file within local system.

This dissertation will mainly focus on gathering metadata of personal data in standardized format and propose that personal data should be stored, accessed, exchanged and presented. This method will enable users to search while getting instant feedback and suggestions. PAuth provides an offline table — personal repository, which contains all the extended metadata. It enriches metadata of the stored media in personal system (local system). All the fields are multi-purpose and versatile in naming. This method will also suggest how information can be safely exchanged without sacrificing user privacy.

Date of Award	31 Oct 2016
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Hongbo FU (Supervisor), Zhi-Qiang LIU (Supervisor) & Hon Wai CHUN (Supervisor)