Incremental Learning in SwiftFile
نویسندگان
چکیده
SwiftFile is an intelligent assistant that helps users organize their e-mail into folders. SwiftFile uses a text classifier to predict where each new message is likely to be filed by the user and provides shortcut buttons to quickly file messages into one of its predicted folders. One of the challenges faced by SwiftFile is that the user’s mail-filing habits are constantly changing — users are frequently creating, deleting and rearranging folders to meet their current filing needs. In this paper, we discuss the importance of incremental learning in SwiftFile. We present several criteria for judging how well incremental learning algorithms adapt to quickly changing data and evaluate SwiftFile’s classifier using these criteria. We find that SwiftFile’s classifier is surprisingly responsive and does not require the extensive training that is often assumed in most learning systems.
منابع مشابه
A Hybrid Framework for Building an Efficient Incremental Intrusion Detection System
In this paper, a boosting-based incremental hybrid intrusion detection system is introduced. This system combines incremental misuse detection and incremental anomaly detection. We use boosting ensemble of weak classifiers to implement misuse intrusion detection system. It can identify new classes types of intrusions that do not exist in the training dataset for incremental misuse detection. As...
متن کاملOn the effect of low-quality node observation on learning over incremental adaptive networks
In this paper, we study the impact of low-quality node on the performance of incremental least mean square (ILMS) adaptive networks. Adaptive networks involve many nodes with adaptation and learning capabilities. Low-quality mode in the performance of a node in a practical sensor network is modeled by the observation of pure noise (its observation noise) that leads to an unreliable measurement....
متن کاملSwiftFile: An Intelligent Assistant for Organizing E-Mail
While most e-mail clients allow users to file messages into folders, the process they must go through to file each message is often tedious and slow. For each message, the user must first decide which folder is most appropriate. Then, the user must inform the e-mall reader of that choice by selecting the appropriate icon or menu item from among what is typically a set of several dozen choices. ...
متن کاملDistributed Incremental Least Mean-Square for Parameter Estimation using Heterogeneous Adaptive Networks in Unreliable Measurements
Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fraction of the nodes, defi...
متن کاملA Note on the Utility of Incremental Learning
Historically, inductive machine learning has focused on nonincremental learning tasks, i.e., where the training set can be constructed a priori and learning stops once this set has been duly processed. There are, however, a number of areas, such as agents, where learning tasks are incremental. This paper defines the notion of incrementality for learning tasks and algorithms. It then provides so...
متن کامل