Mining the Web�@�֍u�����R�E�X�P�W���[��
�����j�b�e�C�͂P�R�}�����N�R�O���y�[�W����L�W�������g�N�����^�Ă܂����B�e�X�I�m�I�m�A�R�O���t���O���[���S�����\�n�b�s���E�������l�K�����܂��B �i���V���`���N���W���E�L���E�����I�E�����K�X�e�L�M�X�P�W���[�����O�|�}�G�_�I���A�����������E�V����ړ��C�h�E���܂��B���ꂩ��T���K�c�W���j�`�A�U���K�c�Q�U���j�`���x�u�L���E�R�E�ł��B�e�l���蓖�Ă�ꂽ���e���AA4��5���O��ł܂Ƃ߂Ă��������B�t���v���W�F�N�^�[�𖈉�p�ӂ��܂��̂ŁA�g���Ĕ��\���Ă��悢�ł��B
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M. Hersovici, M. Jacovi, Y.S. Maarek, D. Pelleg, M. Shtalheim and S. Ur, The Shark-Search algorithm --- an application: tailored Web site mapping, in: 7th World-Wide Web Conference, April, 1998, Brisbane, Australia 
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M. Najork and J. L. Wiener. Breadth-first search crawling yields high-quality pages. Proceedings of the 10th International World Wide Web Conference, May 2001.
Jeffrey Dean, Monika Rauch Henzinger: Finding Related Pages in the World Wide Web. WWW8 / Computer Networks 31(11-16): 1467-1479 (1999)
Soumen Chakrabarti, Martin van den Berg, Byron Dom: Focused Crawling: A New Approach to Topic-Specific Web Resource Discovery. WWW8 / Computer Networks 31(11-16): 1623-1640 (1999)
Michelangelo Diligenti, Frans Coetzee, Steve Lawrence, C. Lee Giles, Marco Gori: Focused Crawling Using Context Graphs. VLDB 2000: 527-534
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2 CRAWLING THE WEB 17 �@ �@ �@
2.1 HTML and HTTP Basics 18 �@ �@ �@
2.2 Crawling Basics 19 5 �A�R�E�G���}�@�W���V���X�P �@
2.3 Engineering Large-Scale Crawlers 22 13 �����^�`�U���@�G�W�q�f�A�L 4��24��
2.4 Putting Together a Crawler 35 �@ �@ �@
2.5 Bibliographic Notes 40 10 Somboonviwat�@Kulwadee �@
3 WEB SEARCH AND INFORMATION RETRIEVAL 45 �@ �@ �@
3.1 Boolean Queries and the Inverted Index 45 8 �X�������V�^ �@
3.2 Relevance Ranking 53 14 �X�������V�^ 5��1��
3.3 Similarity Search 67 �@ �@ �@
3.4 Bibliographic Notes 75 12 �����T�K�@�����i�I�� �@
4 SIMILARITY AND CLUSTERING 79 �@ �@ �@
4.1 Formulations and Approaches 81 �@ �@ �@
4.2 Bottom-Up and Top-Down Partitioning Paradigms 84 10 ��J�I�I�^�j�@���~�t�` 5��15��
4.3 Clustering and Visualization via Embeddings 89 10 ���I�I���l�c�^�@�T�����E�C�` �@
4.4 Probabilistic Approaches to Clustering 99 16 ���L���@���W�������q�f 5��22��
4.5 Collaborate Filtering 115 �@ �@ �@
4.6 Bibliographic Notes 121 10 �ēc���l�_�@���������E�C�` �@
5 SUPERVISED LEARNING 125 �@ �@ �@
5.1 The Supervised Learning Scenario 126 �@ �@ �@
5.2 Overview of Classification Strategies 128 �@ �@ �@
5.3 Evaluating Text Classifiers 129 �@ �@ �@
5.4 Nearest Neighbor Learners 133 11 ���i�X�G�i�K�@�K���R�E�w�C �@
5.5 Feature Selection 136 11 �x���g�~�I�J�@���������E�^ 5��29��
5.6 Bayesian Learners 147 �@ �@ �@
5.7 Exploiting Hierarchy among Topics 155 13 �����I�K�~�@�_���R�E�C�` �@
5.8 Maximum Entropy Learners 160 �@ �@ �@
5.9 Discriminative Classification 163 9 �V�H�A�}�n�@�����P���C�` �@
5.10 Hypertext Classification 169 �@ �@ �@
5.11 Bibliographic Notes 173 8 �����ف@���� 6��5��
6 SEMI SUPERVISED LEARNING 177 �@ �@ �@
6.1 Expectation Maximization 178 7 �����i�J�����@�m�����E�X�P �@
6.2 Labeling Hypertext Graphs 184 11 �ΐ��C�V�J���@�m�`���C�` �@
6.3 Co-training 195 �@ �@ �@
6.4 Bibliographic Notes 198 8 ���I�I�O���@���^�J�V���W 6��12��
7 SOCIAL NETWORK ANALYSIS 203 �@ �@ �@
7.1 Social Sciences and Bibliometry 205 �@ �@ �@
7.2 PageRank and HITS 209 16 �����R�j�V�@�N���R�E�X�P �@
7.3 Shortcomings and the Coarse-Grained Graph Model 219 �@ �J���^�j�O�`�@�q���g���� 6��19��
7.4 Enhanced Models and Techniques 225 16 �X�������V�^ �@
7.5 Evaluation of Topic Distillation 235 8 ���^�C�@�����E���w�C �@
7.6 Measuring and Modeling the Web 243 �@ �@ �@
7.7 Bibliographic Notes 254 12 ���u�c�J���V�_�@�ǘa���V�J�Y 7��3��
8 RESOURCE DISCOVERY 255 �@ �@ �@
8.1 Collecting Important Pages Preferentially 257 �@ �@ �@
8.2 Similarity Search Using Link Topology 264 13 ���X���T�T�L�@�L�V�� �@
8.3 Topical Locality and Focused Crawling 268 16 �ē��T�C�g�E�@���Y�^���E �@
8.4 Discovering Communities 284 �@ �@ �@
8.5 Bibliographic Notes 288 �@ �@ �@
9 THE FUTURE OF WEB MINING 289 �@ �@ �@
9.1 Information Extraction 290 11 �����n���c�@���a�}�T�J�Y 7��10��
9.2 Natural Language Processing 295 �@ �@ �@
9.3 Question Answering 302 �@ �@ �@
9.4 Profiles, Personalization, and Collaboration 305 �@ �@ �@
9.end �@ 306 12 �ɓ� �G�a  7��17��
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