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Patent

Harnessing information about the timing of a user's client-server interactions to enhance messaging and collaboration services

TLDR
In this paper, a system and method is provided to facilitate communication and collaboration by considering the timing of a user's activities on one or more clients via accessing, from a centralized server, information about the user's client-server interactions.
Abstract
A system and method is provided to facilitate communication and collaboration by considering the timing of a user's activities on one or more clients via accessing, from a centralized server, information about the user's client-server interactions. The systems and methods can harness existing protocols and data exchange used in legacy client-server applications for email, making available to one or more client-side message routing applications, information about a user's interactions with email across multiple clients. Applications include considering the time since the last client-server interaction to guide decisions about if, when, and how to route messages so as to limit the mobile relay of information a user has already seen, providing information to colleagues about a user's current or past “inbox presence,” and forecasting the time until a user will have access to a device or communication channel.

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Citations
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References
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Book ChapterDOI

Text Categorization with Suport Vector Machines: Learning with Many Relevant Features

TL;DR: This paper explores the use of Support Vector Machines for learning text classifiers from examples and analyzes the particular properties of learning with text data and identifies why SVMs are appropriate for this task.
Book

Fast training of support vector machines using sequential minimal optimization

TL;DR: In this article, the authors proposed a new algorithm for training Support Vector Machines (SVM) called SMO (Sequential Minimal Optimization), which breaks this large QP problem into a series of smallest possible QP problems.
Proceedings Article

Empirical analysis of predictive algorithms for collaborative filtering

TL;DR: Several algorithms designed for collaborative filtering or recommender systems are described, including techniques based on correlation coefficients, vector-based similarity calculations, and statistical Bayesian methods, to compare the predictive accuracy of the various methods in a set of representative problem domains.
Journal ArticleDOI

The active badge location system

TL;DR: A novel system for the location of people in an office environment is described, where members of staff wear badges that transmit signals providing information about their location to a centralized location service, through a network of sensors.
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