Why and how CARPE should be personal?

Abstract

In this paper, the significance of modeling human personalities is analyzed for improving the value proposition of solutions for Capturing, Archiving and Retrieval of Personal Experiences (CARPE). Differences in human personalities have a significant and often an overriding impact on how raw events are linked and organized into threads of experiences. Recommendations and predictions are presented on how existing technologies and current research can be integrated for this purpose. The focus here is on the importance of using techniques for improving the quality of the experience thread formation from the raw stream of observation content and on harvesting personality information from analyzing the captured content. Personality models are used when clustering raw event content into such threads. The resulting threads will represent the subject's experience in view of the subjects' personality. The formations of the CARPE threads also contribute to the development of the personality. As a result, the real-life experience view of the subsequently built threads is further enhanced. Also discussed are ways of integrating various methods of building and integrating such models using personality profiling.

Declarative Consciousness for Reconstruction

“…Figure 1 illustrates the different category layers of data as constituents of a human person"s mind and behavior. In more details, these were described in some of the previous investigations on how to represent a person as data (Seymour L. G., 2005), The top layer, "Observed Experience Content Representation" gained as direct personal observations by various Lifelogging devices, such as the currently emerging Google Glass and Memoto wearable devices and technologies (Bell G., 2004) (Seymour L. G., 2005), and in a broader sense, using Quantified Self ( QS ) data input. These do not require any special professional domain expertise to interpret when consuming the data by human sensory organs, although in some cases, some QS measurement interpretations do assume some degree of understanding of some fields of medicine.…”

“…Personhood high-level model derived from LifeLogs (Seymour L. G., 2005). This layer is derived by analytics from the first stage data and these were represented in the middle two layers of Figure 1.…”

“…The idea of collecting digitized personal experiential data for the purpose of building a digital persona model of individuals as a specific of the "generic" persona models has been already disclosed close to a decade ago (Seymour L. G., 2005). The idea illustration is shown in Figure 3 below.…”

“…LifeLog R&D commenced over a decade ago, pioneered by Gordon Bell's 'MyLifeBits' program at Microsoft Research (Bell G., 2004) and then, the social media explosion and Quantified Self (QS) community growth made it ubiquitous. With a few years of delay, the idea of using LifeLog data for analytics derived universal persona model data emerged (Seymour L. G., 2005), while monetizing fragments of such persona models became commonplace in the industry in the form of "personality profiling", "behavioral analytics" and "sentiment mining" for CRM ( Customer Relationship Management ), safety and security surveillance, and most recently for "personalized medicine" and life-style coaching. While tremendous application opportunities were discovered by utilizing IT models in psychoanalytic research (Oren T.I., 2003) the application of computing technologies in other human-centric disciplines brought fundamental transitions in these traditionally distinct fields, resulting in the development of computational biomedicine, computational neuroscience, computational genomics, computational 'Omics' ( Snyder ), etc.…”