Semantic Networks of Mobile Life-Log for Associative Search Based on Activity Theory

Recently, due to proliferation of mobile devices, we can collect users’ life-log. Human long-term memory is an interconnected network. The retrieval system of it is cue-dependent. Semantic networks are used to implement it of human retrieval system. It is possible to retrieve relevant data more effectively by using a search system based on network visualization which provides relations among data rather than a text-based search system. This paper proposes representation of semantic networks of mobile life-log based on activity theory, and associatively finds data based on network visualization for it. We have implemented the system, searched data from an example of search, and performed a subjective test. As a result, we have confirmed that this system is useful for associative retrieval resembled to human cue-dependent recall.