Conference Paper

Information "uptrieval": exploring models for content assimilation and aggregation for developing regions.

DOI: 10.1145/1367497.1367755 Conference: Proceedings of the 17th International Conference on World Wide Web, WWW 2008, Beijing, China, April 21-25, 2008
Source: DBLP


Information Retrieval on the WWW is important because it is hard to nd what one is looking for. There is a plethora of information available, and searching relevant information is a challenge. In the case of developing regions, we have the opposite problem: (1) Information availability of global markets is scarce. Most of the consumers and producers (of information as well as goods) are relegated to local mar- kets in geographical vicinity. In order to reach wider mar- kets, it is important for this local information to reach wider audiences. (Local information for global consumption LIG model). (2) At the same time, locally relevant information, such as delays in bus/train timings, mobile medical van schedule changes, electricity outage timings, is not easily available either. (Local information for local consumption LIL model). We introduce the term Information Uptrieval to address the reverse problem of acquiring, assimilating, ag- gregating and uploading global and local information that is relevant for developing regions to a platform that improves the reach of the information. While the WWW is an ob- vious example of one such platform, given the low internet penetration in such regions, we need to explore eectiv e al- ternatives. Several innovative, but disconnected approaches have been attempted to address the information uptrieval problem, ranging from the use of DVDs1 through the use of wireless stations on motorcycles2. Many of these have met with reasonable success in their pilot deployments.

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Available from: Arun Kumar, Aug 12, 2014
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    ABSTRACT: In the developing regions much of local information content is not available in form seasily indexable by web crawlers. In this paper we describe a new local data uploading system called Information Uptriever. The goal of Information Uptriever is to selectively upload local data relevant to a pre-defined set of decision-making situations. Rather than uploading normal (or all) information that does not necessarily result in an immediate action an Information Uptriever uploads actionable information that is likely to be most relevant in a decision-making situation and may lead to action. Using freely available resources on the web we implement the system for uploading actionable information pertaining to the domain of Indian higher education as a proof-of-concept. Our anecdotes suggest that uptrieving is very effective for uploading information relevant to a pre-defined set of actions. The live system is accessible at
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