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Making large-scale support vector machine learning practical
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Focused crawling: a new approach to topic-specific Web resource discovery
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Authoritative sources in a hyperlinked environment
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SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
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ECML '98 Proceedings of the 10th European Conference on Machine Learning
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IEEE Pervasive Computing
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Concurrency and Computation: Practice & Experience
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WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Introduction to Information Retrieval
Introduction to Information Retrieval
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ACM Computing Surveys (CSUR)
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CHI '09 Extended Abstracts on Human Factors in Computing Systems
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Proceedings of the 18th international conference on World wide web
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AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A)
WiLdnet: design and implementation of high performancewifi based long distance networks
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Economic analysis of networking technologies for rural developing regions
WINE'05 Proceedings of the First international conference on Internet and Network Economics
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Proceedings of the 4th Annual Symposium on Computing for Development
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This paper presents a system for enabling offline web use to satisfy the information needs of disconnected communities. We describe the design, implementation, evaluation, and pilot deployment of an automated mechanism to construct Contextual Information Portals (CIPs). CIPs are large searchable information repositories of web pages tailored to the information needs of a target population. We combine an efficient classifier with a focused crawler to gather the web pages for the portal for any given topic. Given a set of topics of interest, our system constructs a CIP containing the most relevant pages from the web across these topics. Using several secondary school course syllabi, we demonstrate the effectiveness of our system for constructing CIPs for use as an education resource. We evaluate our system across several metrics: classification accuracy, crawl scalability, crawl accuracy and harvest rate. We describe the utility and usability of our system based on a preliminary deployment study at an after-school program in India, and also outline our ongoing larger-scale pilot deployment at five schools in Kenya.