Context-aware Retrieval: Exploring a New Environment for Information Retrieval and Information Filtering

Personal and Ubiquitous ComputingPublished 1 December 2001

Peter J. Brown, Gareth J. F. Jones

DOI10.1007/s007790170004

Source URL

Citations140

SJR quartileQ2

SJR score0.54

SNIP0.95

TL;DR

The thesis is that context-aware retrieval is as yet a sparsely researched and sparsely understood area, and this paper aims to make a start towards remedying this.

Abstract

The opportunities for context-aware computing are fast expanding. Computing systems can be made aware of their environment by monitoring attributes such as their current location, the current time, the weather, or nearby equipment and users. Context-aware computing often involves retrieval of information: it introduces a new aspect to technologies for information delivery; currently these technologies are based mainly on contemporary approaches to information retrieval and information filtering. In this paper, we consider how the closely related, but distinct, topics of information retrieval and information filtering relate to context-aware retrieval. Our thesis is that context-aware retrieval is as yet a sparsely researched and sparsely understood area, and we aim in this paper to make a start towards remedying this.

Keywords

Computer Science

Information Processing & ManagementTerm-weighting approaches in automatic text retrieval

9,532 Citations1988Gerard Salton, Chris Buckley

This paper summarizes the insights gained in automatic term weighting, and provides baseline single term indexing models with which other more elaborate content analysis procedures can be compared.

Context-Aware Computing Applications

3,165 Citations1994Bill N. Schilit, Norman I. Adams +1 more

Communications of the ACMInformation filtering and information retrieval

1,288 Citations1992Nicholas J. Belkin, W. Bruce Croft

Models of information retrieval and filtering, and lessons for filtering from retrieval research are presented; users see only the data that is extracted.

View PDF

IEEE Personal CommunicationsContext-aware applications: from the laboratory to the marketplace

744 Citations1997Peter J. Brown, J.D. Bovey +1 more

The aim of this article is to factor out a simple class of context-aware applications and make the creation of these as easy as, say, creating Web pages.

Personal and Ubiquitous ComputingThe wearable remembrance agent: A system for augmented memory

361 Citations1997Bradley J. Rhodes

The wearable remembrance agent is described, a continuously running proactive memory aid that uses the physical context of a wearable computer to provide notes that might be relevant in that context.

PEPYS: Generating Autobiographies by Automatic Tracking

113 Citations1991William M. Newman, Margery Eldridge +1 more

This paper describes an application called Pepys, designed to yield descriptions of episodes based on automatically collected location data, which pays particular attention to meetings and other episodes involving two or more people.

CL Technical ReportsA probabilistic model of information and retrieval: development and status

104 Citations2021Karen Spärck Jones, Steve Walker +1 more

View PDF

Margin notes

86 Citations2000Bradley J. Rhodes

This paper presents design techniques and heuristics for building “remembrance agents,” applications that watch a user's context and proactively suggest information that may be of use.

Communications of the ACMReactive environments

74 Citations1997Jeremy R. Cooperstock, Sidney Fels +2 more

In the last few years, computer scientists have begun talking about a new approach to human-computer interaction in which computing would not necessitate sitting in front of a screen and isolating ourselves from the world around us, and in a computer-augmented environment, electronic systems could be merged into the physical world to provide computer functionality to everyday objects.

View PDF

Journal of DocumentationThreshold setting in adaptive filtering

48 Citations2000Stephen Robertson, Stephen Walker

Methods for setting appropriate thresholds and adapting them as a result of feedback information on the performance of the profile are discussed, and these methods fit within the probabilism approach to retrieval, and are applied to a probabilistic system.