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an architecture that will allow us to experiment with‘discovering’ rather than coding categories, communities andother interesting semantics based on actual usage.Our system does not require any ontology since it buildssemantic links (infers semantics from links) pragmatically,based on the actual navigation of users. The advantage is thatthe generation and the maintenance of links are dynamic,hence our system adapts dynamically to any change within therepository.Although our system is obviously not suitable fornavigating the whole Web, it is based on generic principlesthat make it adaptable to any sort of repository, from arelational database of learning objects or other resources to alocal area network of web pages.[8] Carnevale, Dan. (2001). “Some online educators turn to bite-sizedinstruction”, Chronicle of Higher Education, May 3, 2001.[Online] http://chronicle.com/free/2001/05/2001050301u.htm[9] Downs, Stephen (May 2000). “Learning objects”. [Online]Accessed: 25 March 2002.(http://www.atl.ualberta.ca/downes/Learning_Objects.doc)[10] http://socci.edna.edu.au/content/index.asp[11] Rosch, E. (1978): Principles of categorization. In E. Rosch & B.B. Lloyd (eds.): Cognition and categorization (pp. 27-48).Hillsdale, NJ: Erlbaum[12] Lakoff, G (1990): Women, Fire and Dangerous Things WhatCategories Reveal about the Mind, University of Chicago Press,ChicagoV. CONCLUSION AND FUTURE WORKCoded metadata or indexing mechanisms fix the contentsemantics of information repositories. We believe that we canenhance users’ experiences in discovering information in richrepositories by using the mechanism described in this paper toderive semantics based on users’ navigations. Of particularinterest is the discovery of communities or categories of bothinformation and users, and uncovering untagged aspects ofcomplex objects relevant to the user community. The businessintelligence layer described in this paper has been designed asa test bed for such experiments.REFERENCES[1] P. Resnick, H.R. Varian, “Recommender systems”,Communications of the ACM, vol. 40 issue 3, p. 56-58, 1997.[2] M. Balabanovic, Y. Shoham, “Fab: Content-Based, CollaborativeRecommendation”, Communications of the ACM, vol. 40 issue 3,March 1997.[3] D.M. Nichols, “Implicit Rating and Filtering”, in Proceedings ofthe 5th DELOS Workshop on Filtering and Collaborative Filtering,10-12 November 1997, Budapest, Hungary.[4] M. Claypool, D. Brown, P. Le, M. Waseda, “Inferring UserInterest”, in IEEE Internet Computing, November/December 2001,p. 32-39.[5] K. Bradley, R. Rafter, B. Smyth, “Inferring Relevance Feedbackfrom Server Logs: A Case Study in Online Recruitment”, 2000, inProceedings of the 11th Irish Conference on Artificial Intelligenceand Cognitive Science (AICS 2000), Galway, Ireland.[6] H. Lieberman, C. Fry, and L. Weitzman, “Exploring the Web withReconnaissance Agents”, in Communications of the ACM, Volume44 Issue 8, August 2001.[7] Web Ontology Working Group:http://www.w3.org/2001/sw/WebOnt/MSc EMOOSE Thesis – http://www.emn.fr/EMOOSE 64
Appendix D: Source Code1 Agent infrastructure1. Class MAP.Middlewareusing System;using System.Windows.Forms;using System.Diagnostics;namespace MAP{/// /// Utility class for the infrastructure management./// Two configurations are possible: (1) this process on thiscomputer/// is the main host, i.e. the centralized parts of theinfrastructure/// reside in this process, or (2) this process is not the main host:/// it has to communicate with the remote main host for accessing the/// centralized parts of the infrastructure./// These configurations depend on the way the infrastructure isinstalled/// by method Install./// public sealed class Middleware{// For Http Remoting operationsinternal static readonly int SERVER_PORT = 1989;internal static readonly int CLIENT_PORT = 1990;0, 5);// Maximum latency time of network for Messages to be deliveredpublic static readonly TimeSpan MAX_LATENCY = new TimeSpan(0,/// /// The address of the current process on this machine./// public static readonly AgentAddress ThisAddress = newAgentAddress(GetProcessId(), GetComputerName());thehost,/// /// The name of the main host machine, i.e. the one on which/// NS and the DF should reside. If this process is the main/// then the value is "localhost"./// private static string MAIN_HOST;/// /// Returns the name of this computer./// /// public static string GetComputerName(){MSc EMOOSE Thesis – http://www.emn.fr/EMOOSE 65
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Vrije Universiteit Brussel - Belgiu
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ContentsAbstract 1Acknowledgements
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(4) Table UP_SUP (matches User Prof
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content providers’ interpretation
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- Active profiling consists in aski
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2 Agents2.1 Overview2.1.1 Definitio
Page 15 and 16: (1) each agent has incomplete infor
Page 17 and 18: MASs need an organization for speci
Page 19 and 20: However, the usefulness of personal
Page 21 and 22: they often provide implementation o
Page 23 and 24: 2.5 Design2.5.1 The DIMA designIn [
Page 25 and 26: 3 MetadataDuring the earlier invest
Page 27 and 28: This requires some agreement and st
Page 29 and 30: 4 PerspectivesRecommender systems m
Page 31 and 32: way Lego blocks should be assembled
Page 33 and 34: usiness intelligence is generated.
Page 35 and 36: important than memory space optimiz
Page 37 and 38: The graph is then formatted to be v
Page 39 and 40: Chapter 4: Implementation1 Implemen
Page 41 and 42: (1) A Name Server (NS) maps every a
Page 43 and 44: the agent terminates, the thread is
Page 45 and 46: 4 Application level4.1 OverviewThe
Page 47 and 48: 4.3 User Agent MakerThis agent has
Page 49 and 50: Thus the profile, node and link cla
Page 51 and 52: BIProviderR : Provide_Business_Inte
Page 53 and 54: to enable users to explicitly speci
Page 55 and 56: ConclusionA “minimalist” approa
Page 57 and 58: Appendix A: Addendum onIndustrial I
Page 59 and 60: Appendix B: SQL Tables Design1 Tabl
Page 61 and 62: Appendix C: Conference PaperA paper
Page 63 and 64: very large repositories of learning
Page 65: popularity of the link (the bigger
Page 69 and 70: public static bool ProcessIsMainHos
Page 71 and 72: string path = MakePath(".", Middlew
Page 73 and 74: System.Messaging.MessageQueue queue
Page 75 and 76: public static NameServer GetNS(){if
Page 77 and 78: }}}table[agentId] = address;}}/// /
Page 79 and 80: ****** NON-STATIC PART ******// Tab
Page 82 and 83: }}}return (AgentId) first;using Sys
Page 85 and 86: {}return Subject.GetHashCode() + Na
Page 87 and 88: name in order to allow for the retr
Page 89 and 90: }// Start agent's main Thread.Threa
Page 91 and 92: }DirectoryFacilitator.GetDF().Unreg
Page 93 and 94: {/// /// Allows for specific conver
Page 95 and 96: }Monitor.Exit(aLock);public overrid
Page 97 and 98: Allows for synchronized Message exc
Page 99 and 100: esource./// /// public string GetMa
Page 101 and 102: }}private void RunTerminationExamin
Page 103 and 104: }private Message RequestUACreation(
Page 105 and 106: }msgQueue.AddFilters(new MessageCat
Page 107 and 108: Message received: interrupt preterm
Page 109 and 110: 19. Class Architecture.DBManagerAg
Page 111 and 112: }}connection.Close();/// /// For sa
Page 113 and 114: using System.Collections;namespace
Page 115 and 116: namespace Architecture.Profiles{usi
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private UP(DataRow row) : this(newU
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}DataRow[] rows = Row.GetChildRows(
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}adapter.Update(Data);//***********
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internal static readonly string LAS
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}}Row[OCCURRENCES] = Occurrences +
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}get{}return Data.Rows.Find(_name);
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private static SqlDataAdapter adapt
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}foreach (ILink link in links){if (
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}}}private DataRow Row{get{return D
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18. N. Good, et al. Combining colla
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49. D. Derbyshire, et al., Agent-Ba
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83. Council for Higher Education Ac
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