Personal Web Revisitation by Context and Content Keywords with Relevance Feedback
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ABSTRACT :
Getting back to previously viewed web pages is a common yet uneasy task for users due to the large volume of personally
accessed information on the web. This paper leverages human’s natural recall process of using episodic and semantic memory cues
to facilitate recall, and presents a personal web revisitation technique called WebPagePrev through context and content keywords.
Underlying techniques for context and content memories’ acquisition, storage, decay, and utilization for page re-finding are discussed. A
relevance feedback mechanism is also involved to tailor to individual’s memory strength and revisitation habits. Our 6-month user study
shows that: (1) Compared with the existing web revisitation tool Memento, History List Searching method, and Search Engine method,
the proposed WebPagePrev delivers the best re-finding quality in finding rate (92.10%), average F1-measure (0.4318) and average
rank error (0.3145). (2) Our dynamic management of context and content memories including decay and reinforcement strategy can
mimic users’ retrieval and recall mechanism. With relevance feedback, the finding rate of WebPagePrev increases by 9.82%, average
F1-measure increases by 47.09%, and average rank error decreases by 19.44% compared to stable memory management strategy.
Among time, location, and activity context factors in WebPagePrev, activity is the best recall cue, and context+content based re-finding
delivers the best performance, compared to context based re-finding and content based re-finding.