Fast, flexible filtering with phlat

Abstract

Systems for fast search of personal information are rapidly becoming ubiquitous. Such systems promise to dramatically improve personal information management, yet most are modeled on Web search in which users know very little about the content that they are searching. We describe the design and deployment of a system called Phlat that optimizes search for personal information with an intuitive interface that merges search and browsing through a variety of associative and contextual cues. In addition, Phlat supports a unified tagging (labeling) scheme for organizing personal content across storage systems (files, email, etc.). The system has been deployed to hundreds of employees within our organization. We report on both quantitative and qualitative aspects of system use. Phlat is available as a free download at http://research.microsoft.com/adapt/phlat. Author KeywordsPersonal information management, user interfaces, interactive information retrieval, tagging. ACM Classification KeywordsH5.2. Information interfaces and presentation (e.g., HCI). specific permission and/or a fee.

Retrieval experiments using pseudo-desktop collections

“…Desktop search systems such as Stuff I've Seen [9] and Phlat [8] showed that user interaction is a significant issue in the desktop environment, and that date is most important feature since most users sorted the results by date. Other researchers focused more on improving the quality of ranking and proved that temporal locality and causality [18] are useful features.…”

“…The criteria that we used for the documents in a desktop were that the documents should be related to a particular person, there should be of a variety of document types, the different document types should have metadata or fields, and that the collection should be of reasonable size, although there is no hard limit on size since real-world desktops vary considerably. [8] The privacy of the target individual was another concern.…”

“…Past research efforts in this area have focused on the discovery of desktop-specific features [19] and desirable characteristics for user interfaces [9] [8]. This research has been limited by the lack of availability of shareable test collections.…”

“…This research has been limited by the lack of availability of shareable test collections. For instance, desktop search prototypes such as Stuff I've Seen [9], Phlat [8] and Connections [18] employ evaluation methods based on real users' desktop collections and queries, distributing prototype search engines to users, and evaluating performance with logged usage data. This type of evaluation is certainly valuable as it is based on actual use cases.…”

Professional Knowledge Management

“…LFAi sb ased on recorded user interactions with aP IM tool, normally in naturalistic conditions out-with the control of the experimenter[ DCC + 03, CRDS06,TAJP07]. LFAe xamines the quantitative aspects of user behaviour,i ncluding the nature of submitted queries and the properties of items accessed.…”