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Crowdsourcing Supported Context Detection for Improving Information Search Activities

Authors:
Michael Beul
Stefan Eicker

Keywords: Context Detection; Context Awareness; Information Retrieval; Information Search Process; Collective Intelligence; Crowdsourcing

Abstract:
In environments that require the use of software applications, intervals where application functionality, tools, methods and technical systems are changing are often very short. The process of searching for relevant information about a specific issue is frequently executed and time-consuming. Because of the availability of a nearly unlimited amount of data, people spend a lot of time in formulating search queries and evaluating the relevance of the search results. In this paper, we describe a generic approach that improves the information search and retrieval process of different activities with the use of context information. One main goal is the integration of the crowd€ at different stages of this process by combining collective intelligence concepts with context-aware systems. This combination can be used to automatically reduce information overflow by filtering irrelevant data. Furthermore, a real-time information retrieval process without manual search im pulses is provided. We also present a prototype as a proof of concept in order to validate feasibility and benefit.

Pages: 254 to 259

Copyright: Copyright (c) IARIA, 2012

Publication date: June 24, 2012

Published in: conference

ISSN: 2308-4529

ISBN: 978-1-61208-202-8

Location: Venice, Italy

Dates: from June 24, 2012 to June 29, 2012