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Web Intelligence, 2004. WI 2004. Proceedings. IEEE/WIC/ACM International Conference on

Date 20-24 Sept. 2004

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Displaying Results 1 - 25 of 172
  • [Title page]

    Page(s): i - iv
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    Freely Available from IEEE
  • Table of contents

    Page(s): v - xiii
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  • Message from the WI'04 and IAT'04 Conference Chairs and Program Chair

    Page(s): xiv - xvii
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  • WI'04 and IAT'04 Conference Organizers

    Page(s): xviii - xix
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  • WI'04 and IAT'04 Program Committee Leadership

    Page(s): xx
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  • WI'04 and IAT'04 Program Committee Members

    Page(s): xxi - xxvi
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  • WI'04 Non-Program Committee Reviewers

    Page(s): xxvii
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    Freely Available from IEEE
  • WI'04 and IAT'04 Tutorials and Workshops

    Page(s): xxviii
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (30 KB) |  | HTML iconHTML  

    Provides an abstract for each of the tutorial presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Incentive-Compatible Social Choice

    Page(s): 8 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4856 KB) |  | HTML iconHTML  

    Many situations present a social choice problem where different self-interested agents have to agree on joint, co-ordinated decisions. For example, power companies have to agree on how to use the power grid, and airlines have to agree on how to schedule takeoffs and landings. Mechanisms for social choice are called incentive-compatible when cooperative behavior is optimal for all parties. The most well-known examples of incentive-compatible mechanisms are auctions. However, the party that receives the auction revenue has an incentive to manipulate the outcome to increase the revenue. For example, a power gird operator has an interest to reduce capacity and drive up prices. Conversely, if it provides sufficient capacity to every user it derives no revenue to cover its costs. We present a novel mechanism for social choice that is incentive-compatible without generating a payment surplus. We give several examples of applications where it solves the social choice problem without unwanted incentives, and provides significantly better overall utility than any other known mechanism. View full abstract»

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  • Integration of Business Intelligence Based on Three-Level Ontology Services

    Page(s): 17 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4040 KB) |  | HTML iconHTML  

    Usually, integration of business intelligence (BI) from realistic telecom enterprise is by packing data warehouse (DW), OLAP, data mining and reporting from different vendors together. As a result, BI system users are transferred to a reporting system with reports, data models, dimensions and measures predefined by system designers. As a result of survey, 85% of DW projects failed to meet their intended objectives. In this paper, we investigate how to integrate BI packages into an adaptive and flexible knowledge portal by constructing an internal link and communication channel from top-level business concepts to underlying enterprise information systems (EIS). An approach of three-level ontology services is developed, which implements unified naming, directory and transport of ontology services, and ontology mapping and query parsing among conceptual view, analytical view and physical view from user interfaces through DW to EIS. Experiments on top of real telecom EIS shows that our solution for integrating BI presents much stronger power to support operational decision making more user-friendly and adaptively compared with those simply combining BI products presently available together. View full abstract»

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  • Defending Against Flash Crowds and Malicious Traffic Attacks with An Auction-Based Method

    Page(s): 24 - 28
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (176 KB) |  | HTML iconHTML  

    Flash crowd events (FCEs) and malicious traffic including DDoS and worm attacks present a real threat to the stability of Web services. In this paper, we design a practical defense system that can provide some needed relief from the two types of events and protect the availability of Web services. A novel method of dynamic bandwidth arbitration using Generalized Vickrey auction based on microeconomics is proposed. By adopting this approach, not only the availability of Web services is improved but also the total utility of users can be maximized. Initial simulations have shown that this mechanism is promising direction to control both FCEs and malicious traffic. The presentation in this paper is a first step towards a more rigorous evaluation. View full abstract»

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  • An Empirical Study of Web Interface Design on Small Display Devices

    Page(s): 29 - 35
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB) |  | HTML iconHTML  

    This paper reports an empirical study that explores the problem of finding a highly-efficient, user-friendly interface design method on small display devices. We compared three models using our PDA interface simulator: presentation optimization method, semantic conversion method, and zooming method. A controlled experiment has been carried out to identify the pros and cons of each method. The results show that of the three interface methods, the zooming method is slightly better than the semantic conversion method, while they both outperform the optimizing presentation method. View full abstract»

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  • An Approach for Step-By-Step Query Refinement in the Ontology-Based Information Retrieval

    Page(s): 36 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB) |  | HTML iconHTML  

    In this paper we present a comprehensive approach for the refinement of ontology-based queries, which is based on incrementally (step-by-step) and interactively tailoring a query to the current information needs of a user, whereas these needs are implicitly and on-line elicited by analysing the user's behaviour during the searching process. The gap between a user's need and his query is quantified by measuring several types of query ambiguities. Consequently, in the refinement process a user is provided with a ranked list of refinements, which leads to a decrease of some of these ambiguities. Moreover, by exploiting the ontology background, the approach supports finding "similar" results that can help a user to satisfy his information need. View full abstract»

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  • Logic Programming for Context-Aware Pervasive Computing: Language Support, Characterizing Situations, and Integration with the Web

    Page(s): 44 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (168 KB) |  | HTML iconHTML  

    We characterize situations as constraints on sensor readings expressed in rules. We also introduce an extension of Prolog which we call LogicCAP for programming context-aware applications, where situations are first-class entities. The operator "in-situation" in the language captures a common form of reasoning in context-aware applications, which is to ask if an entity is in a given situation. We show the usefulness of our approach via programming idioms, including defining relations among situations and integration with the Web. View full abstract»

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  • Personal Document Recommendation System Based on Data Mining Techniques

    Page(s): 51 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (472 KB) |  | HTML iconHTML  

    Most existing recommendation systems may not be very effective due to the lack of the adequate knowledge of user's behavior or interests. Some systems are not] efficient enough because of the huge on-line computational demand. In this paper, we propose a personal documents recommendation system that effectively filters the on-line news on WWW for each individual user. The proposed system recommends useful news by employing the profiling techniques of modified content- and collaborative-based filtering. In order to reduce the on-line computation and improve the recommendation quality, we design a tree-based data mining algorithm that treats users' behavior and interest as input and filter the news documents efficiently. View full abstract»

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  • Fuzzy Neural Agents for Online NBA Scouting

    Page(s): 58 - 63
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (136 KB) |  | HTML iconHTML  

    Internet is the focus of the intelligent agent applications. The current status of intelligent agent for the World Wide Web is still in its infancy, but like the Web itself, is evolving constantly. Several agents are being designed and implemented for a variety of tasks in diverse range of applications: managing e-mail, navigating and retrieving information from the Internet, online shopping, electronic business, monitoring stock prices or currency exchanges, etc. In this paper, we present and describe an intelligent service agent that assists an NBA scouting agent in his/her work. The particularity of our agent is not only it retrieves relevant information about NBA players from the Internet for the scouting agent but also it derives metadata from that information, which consist of player performance evaluation and player statistics prediction. View full abstract»

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  • Extracting Precise Link Context Using NLP Parsing Technique

    Page(s): 64 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    Link context has been exploited extensively ever since the advent of the World Wide Web, but the approach to extracting precise link context has not been fully explored and many state-of-the-art extraction methods are based on simplistic heuristics and require ad-hoc parameters. In this paper, we propose a novel two-step extraction model, which aims to systematically derive link context of quality as high as anchor text. In the macroscopic analysis step, a systematic web page structure analysis is performed to locate the content cohesive text region and potential relevant header or header like tags. In the microscopic extraction step, an English parser is used to extract the relevant sentence fragments in the text region and the nearest heading text is encompassed if the need arises. Preliminary experimental results proved our approach's effectiveness. View full abstract»

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  • Rough Set-Aided Feature Selection for Automatic Web-Page Classification

    Page(s): 70 - 76
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    Recently Web-pages on the World Wide Web are explosively increasing, and it is now required for portal sites such as Yahoo! service having directory-style search engines to classify Web-pages into many categories automatically. This paper investigates how rough settheory can help select relevant features for Web-page classification. Our experimental results show that the combination of the rough set-aided feature selection method and the Support Vector Machine with a linear kernel is quite useful in practice to classify Web-pages into many categories because not only the performance gives acceptable accuracy but also the high dimensionality reduction is achieved without depending on arbitrary thresholds for feature selection. View full abstract»

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  • Ontology-Based Scalable and Portable Information Extraction System to Extract Biological Knowledge from Huge Collection of Biomedical Web Documents

    Page(s): 77 - 83
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    Automated discovery and extraction of biological knowledge from biomedical web documents has become essential because of the enormous amount of biomedical literature published each year. In this paper we present an ontology-based scalable and portable information extraction system to automatically extract biological knowledge from huge collection of online biomedical web documents. Our method integrates ontology-based semantic tagging, information extraction and data mining together, automatically learns the patterns based on a few user seed tuples, and then extract new tuples from the biomedical web documents based on the discovered patterns. A novel system SPIE (Scalable and Portable Information Extraction) is implemented and tested on the PuBMed to find the chromatin protein-protein interaction and the experimental results indicate our approach is very effective in extracting biological knowledge from huge collection of biomedical web documents. View full abstract»

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  • Matching and Retrieving Sequential Patterns Under Regression

    Page(s): 84 - 90
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (256 KB) |  | HTML iconHTML  

    Sequential pattern matching and retrieving is of real value. For example, finding stocks in the NASDAQ market whose closing prices are always about $β₀ higher than or β₁ times as that of a given company. The probelm reduces to linear pattern retrieval: given query X, find all sequence Y from database S so that Y = β₀ + β₁ with confidence C. In this paper, we novelly introduce SLR (Simple Linear Regression) model [5,7] to solve this problem. We extend 1-dimensional R^2 to ER^2 for multi-dimensional sequence matching, such as on-line handwritten signature. In addition, we develop SLR+FFT pruning techniques based on SLR to speed up retrieval without incurring any false dismissal. Experimental results show that the pruning ratio of SLR+FFT is efficient (can be above 99%). Experiments on real stocks discovered many interesting patterns. Preliminary test on on-line signature recognition using ER^2 as similarity measure also shows high accuracy. View full abstract»

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