Post on 17-Sep-2018
0Universidade Federal de Santa Catarina
Centro de Ciências da Educação
Programa de Pós-Graduação Em Ciência da Informação
0PCI3214 – Recuperação Inteligente de Informação – 3cr. Prof. Dr. Angel Freddy Godoy Viera
e-mail: recinfor@gmail.com
Ementa: A recuperação inteligente da informação (RII), conceitos básicos, visão lógica
de documentos, processos de recuperação. Modelos de recuperação da informação,
taxonomia. Modelos clássicos, modelos da teoria de conjuntos, modelos algébricos,
modelos probabilísticos, modelo de texto estruturado, modelo browsing. Operações
com texto, pré-processamento, clustering e compressão de texto. Indexação e
recuperação, arquivo invertido, índice de textos, consulta booleana, busca seqüencial,
reconhecimento de padrões, consultas estruturadas. Recuperação inteligente de informação na Web e Bibliotecas Digitais.
Objetivo: Proporcionar um enfoque geral sobre as modernas tecnologias subjacentes
aplicadas para a recuperação inteligente da informação, os principais modelos
existentes e seu uso na Web e bibliotecas digitais.
Conteúdo Programático:
1. Recuperação Inteligente da Informação: Conceitos Básicos. Tarefas do usuário.
Visão Lógica dos documentos. Processos de Recuperação.
2. Modelos de Recuperação da Informação: Taxonomia dos modelos de RI, Modelos
Clássicos, Modelos da teoria de conjuntos, Modelos Algébricos, Modelos
Probabilísticos, Modelos de texto estruturado, Modelos browsing. 3. Operações com Texto: Pré-processamento de documentos, Clustering de
Documentos, Compressão de Texto.
4. Indexação e Recuperação: Arquivo Invertido, índices para Textos, Consulta
Booleana, Busca Seqüencial, Reconhecimento de Padrões, Consultas Estruturadas.
5. Recuperação inteligente de Informação na Web e Bibliotecas Digitais.
Metodologia:
Discussão em grupos, seminários, estudos individuais e coletivos, trabalhos em grupos
e outras modalidades conforme a dinâmica dos grupos.
Avaliação:
Serão consideradas na avaliação: participação em aula (10%), trabalhos individuais ou
grupais e redação de resumos críticos (20%), seminários (30%), elaboração de um
artigo final individual, com tema previamente aprovado pelo professor, relacionado
com os tópicos do conteúdo programático (40%). O artigo final deverá ser entregue
em cópia impressa e digital e apresentado em seminário em data estabelecida no
cronograma da disciplina.
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Information Research: http://informationr.net/ir/
e-Books: http://site.ebrary.com/lib/buufsc/
Ciência da Informação URL: http://www.ibict.br/cionline D-Lib Magazine (Digital Library Magazine) URL:http://www.dlib.org/ Directory of Open Journal: http://www.doj.org/ Latindex - http://www.latindex.unam.mx/ SCIRUS: http://www.scirus.com/
RNP http://www.rnp.br SCOPUS: http://www.scopus.com
Portal de periódicos da CAPES: http://www.periodicos.capes.gov.br/
Cronograma
PCI3214-Recuperação Inteligente da Informação
N
o. 2013
T1
Dia
Mês
Conteúdo
1 08ma
r Apresentação da turma. Discussão do plano de aula. Registro no
Courseware da Disciplina, Distribuição das atividades.
Recuperação Inteligente de Informação. Definição. Principais problemas
estudados pela RI. Principais Abordagens na Pesquisa de RI, Tarefas do
Usuário, representação lógica dos documentos. Processos de Recuperação. Leituras: XIE, Iris. Interactive Information Retrieval in Digital Environments. New
York: IGI Publishing, 2008. p.vi-xv, p.1-20.
BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Modern Information
Retrieval: The concepts and technology behind search. (2d.Ed.) New York:
Addison Wesley, 2010.
Ingwersen,P. Information Retrieval Interaction.London:Taylor Graham,
1992, p.49-60. RIJSBERGEN, C.J. One Introduction. In: Information retrieval. University
of Gasgow, 1995, p.1-6.
2 15ma
r
Modelos de Recuperação de Informação. Modelos Clássicos de RI. Modelo
Booleano, Modelo Vetorial, Modelo Probabilístico, Clustering. Leituras: MANNING, C.D.; RAGHAVAN, P.; SCHUTZE, H. An introduction to
information retrieval. Cambridge: Cambridge University Press, 2008, p.1-
14, p. 201-2016,p.167-180. BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 2. Modeling.
In: Modern Information Retrieval. New York: Addison Wesley, 1999. p.19-
34. INGWERSEN,P. The Traditional IR Research Approach. In: Information
Retrieval Interaction. London: Taylor Graham, 1992, p.72-78
3 22ma
r
Soft Information Retrieval: Aplicação da teoria de conjuntos difusos á
recuperação da informação. Modelo Booleano estendido. Representação
difusa dos documentos. Extensão difusa da linguagem de consulta. Tesauros
difusos. Agrupamento difuso de documentos. Aplicação de redes neurais à
recuperação da informação. Técnicas de aprendizado supervisionado.
Técnicas de aprendizado não supervisionadas. Modelos de Recuperação
Textual Estruturada. Leituras:
CRESTANI, Fabio and PASI,Gabriella. Soft Information Retrieval:
Applications of Fuzzy Set Theory and Neural Networks. In: NeuroFuzzy
Techniques for Intelligent Information Systems. Publisher: Physica Verlag
(Springer Verlag), 1999. BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 2. Modeling.
In: Modern Information Retrieval. New York: Addison Wesley, 1999. p.34-
49. FERNEDA, Edberto. Redes neurais e sua aplicação em sistemas de
recuperação de informação. Ciência da Informação, v.35, n.1, p. 25-30,
jan./abr. 2006. TORRA, Vicenço, MIYAMOTO, Sadaaki, LANAU, Sergi. Exploration of
textual document archives using a fuzzy hierarchical clustering algorithm in
the GAMBAL system . Information Processing & Management, v. 41, n.3,
p. 587-598, maio 2005.
4 05abr Operações com Texto: Pré-processamento de documentos, Análise lexical,
Eliminação de palavras proibidas, Stemming, Seleção de Temos de
Indexação.Linguagem de consulta: Consulta baseado em palavras-chave.
Pattern Matching. Consultas estruturais.
Operações na Consulta. Retroalimentação de relevância e expansão de
consultas. Retroalimentação de relevância e pseudo-retroalimentação de
relevância. Métodos globais para reformulação de consultas.
Leituras:
BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 7 Text
Operations. In: Modern Information Retrieval. New York: Addison Wesley,
1999. p.163-175. CARPINETO, CLAUDIO and ROMANO, GIOVANNI. A Survey of
Automatic Query Expansion in Information Retrieval. ACM Computing
Surveys, Vol. 44, No. 1, Article 1, Publication date: January 2012.
BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 4 Query
Languages. In: Modern Information Retrieval. New York: Addison Wesley,
1999. p.99-112. MANNING, C.D.; RAGHAVAN, P.; SCHUTZE, H. Chapter 9. Relevance
feedback and query expansion. In: An introduction to information retrieval.
Cambridge: Cambridge University Press, 2008, p. 162-177.
5 12abr
Avaliação de SRI. Medidas de Relevância. Recall e Precisão. Medidas
Alternativas. Média harmônica. Medida E. Medidas baseadas nos usuários. Indexação e busca. Arquivo Invertido: busca, construção. Análise
automatizada de textos. Leituras:
Mark Sanderson. Test Collection Based Evaluation of Information Retrieval
Systems. Foundations and Trends in Information Retrieval. Vol. 4, No. 4
(2010) 247–375. DOI: 10.1561/1500000009.
MANNING, C.D.; RAGHAVAN, P.; SCHUTZE, H. Chapter 8. Evaluation
in information retrieval. In: An introduction to information retrieval.
Cambridge: Cambridge University Press, 2008, p. 139-158. BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 3 Retrieval
Evaluation. In: Modern Information Retrieval. New York: Addison Wesley,
1999. p.73-95.
Steven Buchanan and Adeola Salako. Evaluating the usability and
usefulness of a digital library. Library Review. Vol. 58 No. 9, 2009 pp. 638-
651. Kyar Nyo Aye, Ni Lar Thein. Efficient Indexing and Searching
Framework for Unstructured Data. Fourth International Conference on
Machine Vision (ICMV 2011): Machine Vision, Image Processing, and
Pattern Analysis, edited by Zhu Zeng, Yuting Li, Proc. of SPIE Vol.
8349, 83493F , 2012. doi: 10.1117/12.921130 MANNING, C.D.; RAGHAVAN, P.; SCHUTZE, H. Chapter 4. Index
construction. In: An introduction to information retrieval. Cambridge:
Cambridge University Press, 2008, p.61-77.
BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 8 Indexing
and Searching. In: Modern Information Retrieval. New York: Addison
Wesley, 1999. p.191-199
6 19abr
Recuperação de informação na Web. Características do ambiente de
busca na Web. Abordagem da Recuperação de informação na Web.
Spiders Web Inteligentes.
Leituras:
Ricardo Baeza-Yates and Prabhakar Raghavan. Chapter2: Next
Generation Web Search. In: Search Computing: Challenges and
Directions. Berling: Springer-Verlag, 2010. Disponível em:
<http://books.google.com.br/books?id=za12XAILNokC&lpg=PP1&hl=pt-BR&pg=PP1#v=onepage&q&f=false>. Acesso em: 15 mai 2012.
BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 11 Web
Retrieval. In: Modern Information Retrieval: The concepts and technology
behind search. (2d.Ed.) New York: Addison Wesley, 2010. p.449-517.
BAEZA-YATES, Ricardo; RIBEIRO-NETO, Berthier. Chapter 2 User
Interface for search. In: Modern Information Retrieval: The concepts and
technology behind search. (2d.Ed.) New York: Addison Wesley, 2010.
p.449-517.
David Hawking. Web Search Engines: Part 1 and Part 2. Computer.
August 2006. Minnie, D. e Srinivasan, S. Intelligent Search Engine Algorithms on
Indexing and Searching of Text Documents using Text Representation.
2011 International Conference on Recent Trends in Information
Systems.
D. Minnie and S. Srinivasan. Meta Search Engines for Information
Retrieval on Multiple Domains. International Journal of Technology
And Engineering System(IJTES): Jan –March 2011- Vol.2.No.2. MANNING, C.D.; RAGHAVAN, P.; SCHUTZE, H.I. Chapter 19. Web
search basics. In: An introduction to information retrieval. Cambridge:
Cambridge University Press, 2007, p. 385- 408. Eduardo M. Eisman, Víctor López, Juan Luis Castro. Intelligent Web
Navigation Using Virtual Assistants. Proceedings of the 7th Workshop on
Intelligent Techniques for Web Personalization & Recommender Systems
(ITWP'09) Pasadena, California, USA, July 11-17, 2009 In conjunction with
the 21st International Joint Conference on Artificial Intelligence - IJCAI
2009.
7 26abr Aprendizado de Maquina para Recuperação da Informação. Mineração de
Conteúdo Web. Mineração de estrutura da Web. Mineração de Uso da Web. Jiang Yongbo and Zhang Ruili. Intelligent Search Engines Based on
Web Mining. Communication Software and Networks (ICCSN), 2011
IEEE 3rd International Conference.
Brijendra Singh, Hemant Kumar Singh. Web data mining research: a
survey. Computational Intelligence and Computing Research (ICCIC),
2010 IEEE International Conference. ZHAO Jing. Web Mining Application in University Library
Personalized Search Engine. Soft Computing and Pattern Recognition
(SoCPaR), 2011 International Conference. CHEN, Hsinchun; CHAU, Michael. Web Mining: machine learning for
Web applications. In: CRONIN, Blaise(ed.).Annual Review of
Information Science and Technology. Medford: Information Today, Inc.,
2004, v.38, p. 289-329.
8 03ma
i Agentes Inteligentes. Definição. Características. Tipos. Agentes Inteligentes
em bibliotecas digitais. Agentes inteligentes para recuperação da
informação. Agentes assistentes no processo de busca de informação.
Agentes inteligentes em serviços em serviços de bibliotecas. Multi-agentes.
Leituras:
Guoying Liu. The application of intelligent agents in libraries: a survey.
Program: electronic library and information systems, Vol. 45 Iss: 1 pp. 78 –
97, 2011. Jiao Wei-wei, Sun Tie-li, Li Xin and Xu Lin-na. Personalized Information
Service System Based on Multi-agent. Fuzzy Information and Engineering.
2010, AISC 78, pp. 769–776. Yan Li, Fuwen Guo and Xiufeng Wang. Intelligent personalised information
retrieval system based on multi-agent. Int. J. Modelling, Identification and
Control, Vol. 12, Nos. 1/2, 2011.
Yi Xiao, Ming Xiao and Fan Zhang. Intelligent Information Retrieval
Model Based on Multi-Agents. Wireless Communications, Networking and
Mobile Computing, 2007. WiCom 2007. International Conference.
Piotr Jedrzejowicz. Machine Learning and Agents. 5th KES International
Conference on Agent and Multi-Agent Systems: Technologies and
Applications, KES-AMSTA 2011;Manchester; June 2011.
9 10ma
i
Busca e Recuperação colaborativa de informação. Recuperação social da
Informação. Leituras:
Danah M. Boyd and Nicole B. Ellison. Social network sites: Denition,
history, and scholarship. Journal of Computer-Mediated Communication,
13(1), 2007. Peng Li, Bin Wang, Wei Jin, Jian-Yun Nie, Zhiwei Shi and Ben He.
Exploring Categorization Property of Social Annotations for Information
Retrieval. CIKM’11, October 24–28, 2011, Glasgow, Scotland, UK. FOSTER, J.. Collaborative information seeking and retrieval. In: CRONIN,
Blaise (ed.). Annual Review of Information Science and Technology.
Medford: Information Today, Inc., 2006, v.40, p.329-356. Denis Parra, Peter Brusilovsky. Evaluation of Collaborative Filtering
Algorithms for Recommending Articles on CiteULike. Proceedings of the
Workshop on Web 3.0: Merging Semantic Web and Social Web 2009 (SW),
Turin, Italy, June 29, 2009, CEUR Workshop Proceedings, ISSN 1613-
0073. Zheng Ye1, Xiangji Jimmy Huang, Song Jin, and Hongfei Lin. Exploring
Social Annotation Tags to Enhance Information Retrieval Performance.
Lecture Notes in Computer Science, 2010, Volume 6335/2010, 255-266,
DOI: 10.1007/978-3-642-15470-6_27
Zhigang ZHOU. Social Information Retrieval Based on User Interesting
Mining. Journal of Computational Information Systems 7:4 (2011) 1373-
1379 Giovanni Tummarello, Christian Morbidoni. Collaboratively building
structured knowledge with DBin:from del.icio.us tags to an “RDFS
Folksonomy". Proceedings of the Workshop on Social and Collaborative
Construction of Structured Knowledge (CKC 2007) at the 16th International
World Wide Web Conference (WWW2007) Banff, Canada, May 8, 2007. Giuseppe Fenza, Vincenzo Loia, Sabrina Senatore. Agent-assisted Tagging
Aimed at Folkonomy-Based Information Retrieval. Intelligent Agent (IA),
2011 IEEE Symposium
Riina Vuorikari,Rob Koper. Ecology of social search for learning resources.
Campus-Wide Information Systems. Vol. 26 No. 4, 2009, pp. 272-286 Vuorikari,Riina. Can Social Information Retrieval Enhance the Discovery
and Reuse of Digital Educational Content?. RecSys’07, October 19–20,
2007, Minneapolis, Minnesota, USA
10 17ma
i Recuperação de Informação multimídia. Requerimentos. Desafios.
Arquitetura. Padrões de Vídeos e Codificação de Vídeos. Metadados.
Técnicas de Processamento de conteúdo. Avaliação da efetividade de
recuperação de informação de vídeos. Leituras: Alessandro Bozzon and Piero Fraternali. Chapter 8: Multimedia and
Multimodal Information Retrieval. Lecture Notes in Computer Science,
2010, Volume 5950/2010, 135-155, DOI: 10.1007/978-3-642-12310-8_8 Klaus Schoeffmann, Bernard Mérialdo, Alexander G. Hauptmann,
Chong-Wah Ngo, Yiannis Andreopoulos, Christian Breiteneder (Eds.).
Advances in Multimedia Modeling. 18th International Conference,
MMM 2012, Klagenfurt, Austria, January 2012. Proceedings. Xu Chen, Alfred O. Hero and Silvio Savarese. Multimodal Video Indexing
and Retrieval Using Directed Information. IEEE Transactions on
Multimedia, vol. 14, no. 1, 2012. Zygmunt Mazur and Konrad Wiklak. Chapter 22 Music Information
Retrieval on the Internet. Advances in Intelligent and Soft Computing,
2010, Volume 80/2010, 229-243, DOI: 10.1007/978-3-642-14989-4_22 Bashar Tahayna, Saadat Alhashmi, Yandan Wang and Khaled Abbas.
Combining Content and Context Information Fusion for Video
Classification and Retrieval. 2010 2nd International Conference on Signal
Processing Systems (ICSPS). Zhigang Kong and Mounia Lalmas. Using XML Logical Structure to
Retrieve (Multimedia) Objects. Research and Advanced Technology for
Digital Libraries Lecture Notes in Computer Science, 2007, Volume
4675/2007, 100-111, DOI: 10.1007/978-3-540-74851-9_9
Yiwei Cao, Ralf Klamma, and Maziar Khodaei. A Multimedia Service with
MPEG-7 Metadata and Context Semantics. Proceedings9th Workshop on
Multimedia Metadata (WMM'09) in conjunction with the 13th French
Multimedia Conference on Compression and Representation of Audiovisual
Signals (CORESA 2009), Toulouse, France, March 19-20, 2009.
11 24ma
i Apresentação de Seminários e Entrega de Artigos. Fechamento da
Disciplina
2013T1 Inicio: 04/mar./2013 Fim: 24/mai./2013