Title: Activity-based linkage and ranking methods for personal dataspace

Authors: Deependra Kumar Sah; Xiaobo Wu; Mingqi Lv; Hamid Turab Mirza

Addresses: School of Management, Zhejiang University, Hangzhou 310027, P.R. China ' School of Management, Zhejiang University, Hangzhou 310027, P.R. China ' College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, P.R. China ' Department of Computer Science, COMSATS Institute of Information Technology, Lahore 54000, Pakistan; College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, P.R. China

Abstract: This research was conducted to alleviate desktop activity support deficiency, which occurs due to the lack of links between desktop resources. The research exploited information such as associations, contexts, and activity information about accesses to local resources, and translated this information into a personal linkage structure. More specifically, the research presented a novel approach to link and rank desktop resources by analysing users' activities over time, and exploited the associative links of resources from their implicit access patterns. Furthermore, multiple ranking methods, such as frequency of access, recency of access, focus time, and connectivity of resources, were proposed. Prototype systems were also developed, and a user study was conducted to validate the effectiveness of the proposed methods. The results showed that ranking desktop resources by their relevance - as carried out in this research - could improve activity-specific support, as well as overall performance in the area of personal information management.

Keywords: activity based ranking system; activity based linkage; desktop resource; desktop search; personal dataspace; personal information management; ranking algorithm; ranking method; resource linkage; user activity.

DOI: 10.1504/IJMC.2018.091381

International Journal of Mobile Communications, 2018 Vol.16 No.3, pp.266 - 285

Available online: 27 Sep 2017 *

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