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e-book
Pattern recognition has gained significant attention due to the rapid explosion of internet- and mobile-based applications. Among the various pattern recognition applications, face recognition is always being the center of attraction. With so much of unlabeled face images being captured and made available on internet (particularly on social media), conventional supervised means of classifying face images become challenging. This clearly warrants for semi-supervised classification and subspace projection. Another important concern in face recognition system is the proper and stringent evaluation of its capability. This book is edited keeping all these factors in mind. This book is composed of five chapters covering introduction, overview, semi-supervised classification, subspace projection, and evaluation techniques.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Electronic and Information Engineering
- Keywords:
- Human face recognition (Computer science)
- Resource Type:
- e-book
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Presentation
This video was recorded at 5th International Semantic Web Conference (ISWC), Athens 2006. We examine research issues that arise when most information items in an enterprise can be linked to each other via short paths, implicit or explicit. In such high-recall settings, the treatment of metadata management, indexing and ranking needs new attention. Additional issues arise as to the best way to handle updates to the connections, whether on or off the transaction path. Even traditional techniques, such as classification and clustering of documents, which stand to benefit from the extra information provided by the so-called network of meaning, need to be reexamined for how best to exploit the extra information. The talk ends with an examination of some promising avenues for using high recall as a driver for the next wave of business process automation
- Subjects:
- Computing, Data Science and Artificial Intelligence and Management
- Keywords:
- Management information systems Information resources management
- Resource Type:
- Presentation
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Open (Access) Journal-Article
Working adults are entering MBA programs in increasing numbers. Some matriculating professionals have difficulty meeting the competitive rigors of business school life for a variety of reasons. One solution to these challenges is to provide learning support systems geared toward individual student backgrounds and interests. The purpose of this paper is to illustrate a screening process for delivering content in a non-residential MBA program for two diverse academic disciplines: organizational management and accounting. The results show that analytical-based classification techniques can effectively identify marginal students for the purpose of providing additional learning resources. The analysis further shows that intelligent tutors can deliver customized Web-based content at a time convenient to the working professional.
- Subjects:
- Management
- Keywords:
- Management--Study teaching (Higher) Adult education Distance education -- Computer-assisted instruction
- Resource Type:
- Open (Access) Journal-Article
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