Abstract
Human memory often fails. People are frequently beset with questions like "Who is that person? I think I met him in Tokyo last year." Existing memory aid tools cannot well support the recall of names effectively. This paper explores the memory recall enhancement issue from the perspective of memory cue extraction and associative search, and proposes a generic methodology to extract memory cues from heterogeneous, multimodal, physical/virtual data sources. Specifically, we use the contact name recall in the academic community as the target application to showcase our proposed methodology. We further develop an intelligent social contact manager that supports 1) autocollection of rich contact data from a combination of pervasive sensors and Web data sources, and 2) associative search of contacts when humanmemory fails. The system is validated by testing the performance of contact data collection techniques. An empirical user study on contact memory recall is also conducted, through which several findings about contact memorizing and recall are presented. Classic cognitive psychology theories are used to interpret these findings.
| Original language | English |
|---|---|
| Article number | 6692881 |
| Pages (from-to) | 78-91 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Human-Machine Systems |
| Volume | 44 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2014 |
Keywords
- Contact recall
- Memory aid
- Pervasive computing
- Social contact management
- Web intelligence
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