Towards efficient document content sharing in social networks

TL;DR: This paper focuses on the social context annotation (SCA) that was introduced to capture implicit information about the usage of document content in the context of the social network, and presents a ranking algorithm that uses SCA along with user profile information to get more personalized search results.

Abstract: Social network services have enabled the increasing sharing of digital content (e.g., images, videos and audios). However, despite the fact that office documents hold a significant amount of users' digital content, office documents have not yet been sufficiently exploited by social networks. The main reason for this is that existing office document architectures/formats are not open enough for selective access, reuse and commenting of document parts. As a response to this problem we have developed a new document architecture, namely the Semantic Document Architecture (SDArch), which enables the annotation of document content with semantic and social context annotation and provides easy access and reuse of the desired document parts. In this paper we focus on the social context annotation (SCA) that we have introduced to capture implicit information about the usage of document content in the context of the social network. We present a ranking algorithm that uses SCA along with user profile information, to get more personalized search results. The current version of SDArch prototype, which implements the algorithm, is also discussed.