Automatic Assignment of Topical Icons to Documents for Faster File Navigation

Several computer users neither assign names to their documents systematically nor organize them into suitable folders, making it difficult to search for relevant files when needed. While this problem can be addressed in several ways, we explore the novel approach of automated assignment of topical icons to documents in order to cue memory for faster navigation. Specifically, we overlay the currently available generic software-oriented file association icons like Acrobat, Word or Powerpoint on documents with algorithmically assigned icons that are specific to the topical content of the documents. Our pipeline method uses document clustering, significant-phrase extraction, phrase generalization and phrase vector matching for assigning icons to documents. Experimental results show that topical iconification significantly speeds up document navigation time vis-á-vis content-based file naming, in both a controlled laboratory setup as well as in a crowdsourced study. Icons assigned by our algorithm are observed to have satisfactory inter-annotator agreement with respect to their meanings.