An Experimental Framework for Email Categorization and
Management
Kenrick Mock
University of Alaska, Anchorage
3211 Providence Dr.
Anchorage, AK 99508
(907) 786-1956
afkjm@uaa.alaska.edu
ABSTRACT
Many problems are difficult to adequately explore until a
prototype exists in order to elicit user feedback. One such
problem is a system that automatically categorizes and manages
email. Due to a myriad of user interface issues, a prototype is
necessary to determine what techniques and technologies are
effective in the email domain. This paper describes the
implementation of an add-in for Microsoft Outlook 2000 TM that
intends to address two problems with email: 1) help manage the
inbox by automatically classifying email based on user folders, and
2) to aid in search and retrieval by providing a list of email relevant
to the selected item. This add-in represents a first step in an
experimental system for the study of other issues related to
information management. The system has been set up to allow
experimentation with other classification algorithms and the source
code is available online in an effort to promote further
experimentation.
Categories and Subject Descriptors
H.3.3 [Information Storage and Retrieval]: Information Search
and Retrieval – Information Filtering, Retrieval Models. H.4.3
[Applications]: Communications Applications - Electronic
mail
General Terms
Experimentation, Human Factors
Keywords
Email management, filtering, classification
1. INTRODUCTION
Email overload has become a growing problem as more users
embrace online technologies. Time Magazine estimated that 776
billion email messages were sent in 1994, 2.6 trillion sent in 1997,
and 6.6 trillion sent in 2000 [2]. In one study, recipients averaged
around 30 email messages per day [1]. To address this problem,
researchers initially designed systems to automatically classify
incoming email into categories or folders using various machine
learning techniques.
This early work f