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Intelligent Systems, IEEE

Issue 1 • Date Jan-Feb 2003

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Displaying Results 1 - 16 of 16
  • Machine and human performance for single and multidocument summarization

    Publication Year: 2003 , Page(s): 46 - 54
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (340 KB) |  | HTML iconHTML  

    The DUC 2002 evaluation revealed numerous language-processing challenges that impact text summarization. The authors examine the techniques used in a multidocument summarization system they developed and its performance at DUC 2002. They also discuss the need for regularization of human summaries. View full abstract»

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  • Personalizing Web publishing via information extraction

    Publication Year: 2003 , Page(s): 62 - 70
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (794 KB) |  | HTML iconHTML  

    The authors propose a multilingual text-classification and hyperlinking system, Namic, based on a knowledge-based approach to information extraction. Their goal is to enable content-aware management and delivery of Web information. View full abstract»

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  • Automatic ontology-based knowledge extraction from Web documents

    Publication Year: 2003 , Page(s): 14 - 21
    Cited by:  Papers (88)  |  Patents (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2527 KB) |  | HTML iconHTML  

    To bring the Semantic Web to life and provide advanced knowledge services, we need efficient ways to access and extract knowledge from Web documents. Although Web page annotations could facilitate such knowledge gathering, annotations are rare and will probably never be rich or detailed enough to cover all the knowledge these documents contain. Manual annotation is impractical and unscalable, and automatic annotation tools remain largely undeveloped. Specialized knowledge services therefore require tools that can search and extract specific knowledge directly from unstructured text on the Web, guided by an ontology that details what type of knowledge to harvest. An ontology uses concepts and relations to classify domain knowledge. Other researchers have used ontologies to support knowledge extraction, but few have explored their full potential in this domain. The paper considers the Artequakt project which links a knowledge extraction tool with an ontology to achieve continuous knowledge support and guide information extraction. The extraction tool searches online documents and extracts knowledge that matches the given classification structure. It provides this knowledge in a machine-readable format that will be automatically maintained in a knowledge base (KB). Knowledge extraction is further enhanced using a lexicon-based term expansion mechanism that provides extended ontology terminology. View full abstract»

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  • Web services: been there, done that?

    Publication Year: 2003 , Page(s): 72 - 85
    Cited by:  Papers (63)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (500 KB)  

    Web services can be defined as loosely coupled, reusable software components that semantically encapsulate discrete functionality and are distributed and programmatically accessible over standard Internet protocols. Web services have received a lot of hype, the reasons for which are not easily determined. Some of their benefits might even seem to waste away, once we touch on the nitty-gritty details, because Web services per se do not offer a solution to underlying problems. The contributions included in this section delve into some of these issues, including: pitfalls of workflow issues; structuring procedural knowledge into problem-solving methods; discussing how a low initial entry barrier and simple technology are balanced against the long-term goal of easy integration; including semantics in a Web service modeling framework; and building on new kinds of applications such as grid enterprises. View full abstract»

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  • Finding the WRITE stuff: automatic identification of discourse structure in student essays

    Publication Year: 2003 , Page(s): 32 - 39
    Cited by:  Papers (8)  |  Patents (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (389 KB) |  | HTML iconHTML  

    An essay-based discourse analysis system can help students improve their writing by identifying relevant essay-based discourse elements in their essays. Our discourse analysis software, which is embedded in Criterion, an online essay evaluation application, uses machine learning to identify discourse elements in student essays. The system makes decisions that exemplify how teachers perform this task. For instance, when grading student essays, teachers comment on the discourse structure. Teachers might explicitly state that the essay lacks a thesis statement or that an essay's single main idea has insufficient support. Training the systems to model this behavior requires human judges to annotate a data sample of student essays. The annotation schema reflects the highly structured discourse of genres such as persuasive writing. Our discourse analysis system uses a voting algorithm that takes into account the discourse labeling decisions of three independent systems. View full abstract»

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  • ITS, eh! Meet Canada's flagship ITS centre and testbed

    Publication Year: 2003 , Page(s): 86 - 89
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (490 KB)  

    This article provides an example of Canadian joint research and deployment efforts in ITS. The University of Toronto and Toronto Transportation Authorities have defined a common testbed for studying and validating possible joint actions to reduce travel time and improve transportation quality, therefore saving on fuel as well. View full abstract»

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  • The limitations of limitations

    Publication Year: 2003 , Page(s): 94 - 97
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (302 KB) |  | HTML iconHTML  

    The authors consider human-centered computing, and argue that human factors and applied cognitive psychologists have not just been selective in regarding certain human characteristics as limitations, but have also selected the wrong things and for the wrong reasons. View full abstract»

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  • Ontology learning and its application to automated terminology translation

    Publication Year: 2003 , Page(s): 22 - 31
    Cited by:  Papers (66)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (722 KB) |  | HTML iconHTML  

    Our OntoLearn system is an infrastructure for automated ontology learning from domain text. It is the only system, as far as we know, that uses natural language processing and machine learning techniques, and is part of a more general ontology engineering architecture. We describe the system and an experiment in which we used a machine-learned tourism ontology to automatically translate multiword terms from English to Italian. The method can apply to other domains without manual adaptation. View full abstract»

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  • Intelligent indexing of crime scene photographs

    Publication Year: 2003 , Page(s): 55 - 61
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB) |  | HTML iconHTML  

    The Scene of Crime Information System's automatic image-indexing prototype goes beyond extracting keywords and syntactic relations from captions. The semantic information it gathers gives investigators an intuitive, accurate way to search a database of cases for specific photographic evidence. Intelligent, automatic indexing and retrieval of crime scene photographs is one of the main functions of SOCIS, our research prototype developed within the Scene of Crime Information System project. The prototype, now in its final development and evaluation phase, applies advanced natural language processing techniques to text-based image indexing and retrieval to tackle crime investigation needs effectively and efficiently. View full abstract»

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  • Speaking the users' languages

    Publication Year: 2003 , Page(s): 40 - 45
    Cited by:  Papers (8)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (826 KB) |  | HTML iconHTML  

    The authors describe a system that generates descriptions of museum objects tailored to the user. The texts presented to adults, children, and experts differ in several ways, from the choice of words used to the complexity of the sentence forms. M-PIRO can currently generate text in three languages: English, Greek, and Italian. The grammar resources are language independent as much as possible. M-PIRO's system architecture is significantly more modular than that of its predecessor ILEX. In particular, the linguistic resources, database, and user-modeling subsystems are now separate from the systems that perform the natural language generation and speech synthesis. View full abstract»

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  • You can tell me by the way I walk

    Publication Year: 2003 , Page(s): 4 - 5
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (673 KB) |  | HTML iconHTML  

    First Page of the Article
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  • Worldwide AI coordination to remain ad hoc

    Publication Year: 2003 , Page(s): 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (286 KB)  

    First Page of the Article
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  • Commercial robots: close but not quite there

    Publication Year: 2003 , Page(s): 6 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1614 KB) |  | HTML iconHTML  

    First Page of the Article
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  • Guest editors' introduction: Recent advances in natural language processing

    Publication Year: 2003 , Page(s): 12 - 13
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | PDF file iconPDF (363 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • 2002 Reviewers

    Publication Year: 2003 , Page(s): 71
    Save to Project icon | Request Permissions | PDF file iconPDF (169 KB)  
    Freely Available from IEEE
  • Bringing semantics to Web services

    Publication Year: 2003 , Page(s): 90 - 93
    Cited by:  Papers (60)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (293 KB) |  | HTML iconHTML  

    A key element to realizing the Semantic Web is developing a suitably rich language for encoding and describing Web content. Such a language must have a well defined semantics, be sufficiently expressive to describe the complex interrelationships and constraints between Web objects, and be amenable to automated manipulation and reasoning with acceptable limits on time and resource requirements. A key component of the Semantic Web services vision is the creation of a language for describing Web services. DAML-S is such a language it is a DAML+OIL ontology for describing Web services that a coalition of researchers created with support from DARPA. View full abstract»

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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.

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Meet Our Editors

Editor-in-Chief
Daniel Zeng
University of Arizona