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Intelligent Systems, IEEE

Issue 3 • Date May-June 2007

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Displaying Results 1 - 20 of 20
  • [Front cover]

    Publication Year: 2007 , Page(s): c1
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    Freely Available from IEEE
  • Table of contents

    Publication Year: 2007 , Page(s): c2
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  • Where Are All the Intelligent Agents?

    Publication Year: 2007 , Page(s): 2 - 3
    Cited by:  Papers (3)
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    Freely Available from IEEE
  • In the News

    Publication Year: 2007 , Page(s): 4 - 7
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  • Karen Spÿrck Jones (1935-2007) [In Memoriam]

    Publication Year: 2007 , Page(s): 8 - 9
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  • Energy and Transportation: A Case Study in China

    Publication Year: 2007 , Page(s): 10 - 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB) |  | HTML iconHTML  

    The Chinese government has made a national priority of developing a sustainable, resource- and energy-efficient society. Because the transportation sector is a major energy consumer with significant opportunities for efficiency improvements, it can play a critical role in achieving this national priority. Here, we summarize current energy consumption patterns and describe one study to improve our understanding of the interactions and dependencies among available resources. We analyzed petroleum, coal, and electricity-based energy consumption data in China's transportation sector from 1990 to 2004. View full abstract»

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  • Improving the Public Health Information Network through Semantic Modeling

    Publication Year: 2007 , Page(s): 13 - 17
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1219 KB) |  | HTML iconHTML  

    The US Centers for Disease Control and Prevention (CDC) created the Public Health Information Network to advance fully capable, interoperable information systems in public health organizations. PHIN prioritizes public health information systems' functional requirements, capabilities, performance measures, and operational characteristics while letting the architects of those systems choose enabling approaches, methods, and concepts to meet the requirements. PHIN also provides a certification process for public health administrators to evaluate their information infrastructure's quality. The certification process is important because affected organizations often depend on certification for continued funding. View full abstract»

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  • Guest Editors' Introduction: Recommender Systems

    Publication Year: 2007 , Page(s): 18 - 21
    Cited by:  Papers (9)
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    Freely Available from IEEE
  • Acquiring and Revising Preferences in a Critique-Based Mobile Recommender System

    Publication Year: 2007 , Page(s): 22 - 29
    Cited by:  Papers (26)  |  Patents (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (601 KB) |  | HTML iconHTML  

    Many e-commerce Web sites offer numerous services, so a product search could return an overwhelming set of options. Without system support, filtering irrelevant products, comparing alternatives, and selecting the best option can be difficult or impossible - especially for users connecting to the Web through a mobile device. Few Web-based recommender systems have been designed for mobile users. A critique-based recommendation methodology aids the acquisition and revision of user preferences in a mobile recommender system. We designed a product recommendation methodology and implemented it in MobyRek, a mobile-phone recommender system that helps users search for travel products. MobyRek supports limited asking and answering of questions and is based mostly on critiques. View full abstract»

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  • Collaborative Filtering Using Dual Information Sources

    Publication Year: 2007 , Page(s): 30 - 38
    Cited by:  Papers (6)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (937 KB) |  | HTML iconHTML  

    Conventional collaborative-filtering methods use only one information source to provide recommendations. Using two sources - similar users and expert users - enables more effective, more adaptive recommendations. Conventional CF methods suffer from a few fundamental limitations such as the cold-start problem, data sparsity problem, and recommender reliability problem. Thus, they have trouble dealing with high-involvement, knowledge-intensive domains such as e-learning video on demand. To overcome these problems, researchers have proposed recommendation techniques such as a hybrid approach combining CF with content-based filtering. Because e-commerce Web sites for e-learning often have various product categories, extracting the many attributes of these categories for content-based filtering is extremely burdensome. So, it might be practical to overcome these limitations by improving the CF method itself. View full abstract»

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  • Informed Recommender: Basing Recommendations on Consumer Product Reviews

    Publication Year: 2007 , Page(s): 39 - 47
    Cited by:  Papers (18)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (326 KB) |  | HTML iconHTML  

    Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology. View full abstract»

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  • New Recommendation Techniques for Multicriteria Rating Systems

    Publication Year: 2007 , Page(s): 48 - 55
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (252 KB) |  | HTML iconHTML  

    Personalization technologies and recommender systems help online consumers avoid information overload by making suggestions regarding which information is most relevant to them. Most online shopping sites and many other applications now use recommender systems. Two new recommendation techniques leverage multicriteria ratings and improve recommendation accuracy as compared with single-rating recommendation approaches. Taking full advantage of multicriteria ratings in personalization applications requires new recommendation techniques. In this article, we propose several new techniques for extending recommendation technologies to incorporate and leverage multicriteria rating information. View full abstract»

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  • Attacks and Remedies in Collaborative Recommendation

    Publication Year: 2007 , Page(s): 56 - 63
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (792 KB) |  | HTML iconHTML  

    Collaborative-filtering recommender systems are an electronic extension of everyday social recommendation behavior: people share opinions and decide whether or not to act on the basis of what they hear. Collaborative filtering lets you scale such interactions to groups of thousands or even millions. Publicly accessible user-adaptive systems such as collaborative recommender systems introduce security issues that must be solved if users are to perceive these systems as objective, unbiased, and accurate. View full abstract»

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  • Attacking Recommender Systems: A Cost-Benefit Analysis

    Publication Year: 2007 , Page(s): 64 - 68
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (934 KB) |  | HTML iconHTML  

    A work highlights the lack of robustness collaborative recommender systems exhibit against attack. This vulnerability can lead to significantly biased recommendations for target items. Here, we examine such attacks from a cost perspective, focusing on how attack size - that is, the number of ratings inserted - affects attack success. We introduce a framework for quantifying the gains attackers realize, taking into account the financial cost of mounting the attack. A cost-benefit analysis of third-party attacks on recommender systems shows that attackers realize profits even when incurring costs associated with rating insertions. View full abstract»

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  • Comparing Recommendation Strategies in a Commercial Context

    Publication Year: 2007 , Page(s): 69 - 73
    Cited by:  Papers (4)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (126 KB) |  | HTML iconHTML  

    From an industrial perspective, recommender systems constitute the base technology for providing interactivity and personalization in electronic business-to-consumer marketplaces. Robin Burke distinguishes between five different recommendation techniques: collaborative, content based, utility based, demographic, and knowledge based. View full abstract»

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  • MarCol: A Market-Based Recommender System

    Publication Year: 2007 , Page(s): 74 - 78
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB) |  | HTML iconHTML  

    Collaborative information-filtering systems maintain user judgments on the relevance of data items.These systems recommend relevant information to other users on the basis of similarity between user profiles or recommended items. This market-based collaborative information-filtering system employs a pricing mechanism to motivate users to provide judgments. Results show that the model increases feedback and improves recommendation quality. MarCol uses Google as the underlying search engine. It stores all user logs, including queries and judgments. View full abstract»

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  • Perceptual (Re)learning: A Leverage Point for Human-Centered Computing

    Publication Year: 2007 , Page(s): 79 - 83
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (129 KB) |  | HTML iconHTML  

    At least since Adrianus Dingeman de Groot conducted his pioneering work on the reasoning of chess masters, perceptual skill has been regarded as key to the advantage of experts. Here we explore the conjunction of two facts: 1. experts can perceive things that are invisible to the novice; 2. it takes a decade or more for someone to become an expert in most significant domains; 3. this conjunction represents a leverage point for intelligent systems - not from the Turing Test perspective of building machines that emulate humans but from the human-centered computing (HCC) perspective of amplifying and extending human capabilities. View full abstract»

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  • Structure Paves the Way to the Semantic Web

    Publication Year: 2007 , Page(s): 84 - 86
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (153 KB) |  | HTML iconHTML  

    The semantic Web, by whatever name it comes to be called, is inevitable. History tells us that as information content grows, so do the mechanisms for organizing and managing it. Over millennia, innovations such as writing systems, alphabetization, pagination, tables of contents, indexes, concordances, reference lookups, classification systems, tables, figures, and statistics have emerged in parallel with content growth. View full abstract»

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  • Calendar/Call for Papers

    Publication Year: 2007 , Page(s): 87 - 88, c3
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  • [Back cover]

    Publication Year: 2007 , Page(s): c4
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Aims & Scope

IEEE Intelligent Systems serves users, managers, developers, researchers, and purchasers who are interested in intelligent systems and artificial intelligence, with particular emphasis on applications.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Daniel Zeng
University of Arizona