Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
2002 Language Engineering Conference
| 2002 Language Engineering Conference |
| Pubbl/distr/stampa | [Place of publication not identified], : IEEE Computer Society Press, 2003 |
| Disciplina | 006.3/5 |
| Soggetto topico |
Natural language processing (Computer science)
Engineering & Applied Sciences Computer Science |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996217941703316 |
| [Place of publication not identified], : IEEE Computer Society Press, 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in digital document processing and retrieval / / editors, Bidyut Baran Chaudhuri, Swapan Kumar Parui, Indian Statistical Institute, India
| Advances in digital document processing and retrieval / / editors, Bidyut Baran Chaudhuri, Swapan Kumar Parui, Indian Statistical Institute, India |
| Autore | Chaudhuri B. B (Bidyut Baran) |
| Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
| Descrizione fisica | 1 online resource (x, 323 pages) : illustrations |
| Disciplina | 025.04 |
| Collana |
Statistical science and interdisciplinary research
Platinum jubilee series |
| Soggetto topico |
Information storage and retrieval systems
Documentation - Data processing Digital preservation Document imaging systems Electronic publishing Multimedia systems Electronic records |
| ISBN | 981-4368-71-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword; Preface; Contents; 1. Document Image Analysis using Markovian Models: Application to Historical Documents; 1.1. Introduction; 1.2. Hidden Markov Random Field Models; 1.2.1. Theoretical foundations; 1.2.1.1. Simulated annealing; 1.2.1.2. Iterated Conditional Modes (ICM); 1.2.1.3. Highest Confidence First (HCF) algorithm; 1.2.1.4. 2D Dynamic Programming; 1.2.2. Application of MRF labelling to handwritten document segmentation; 1.2.2.1. Probability densities; 1.2.2.2. Clique potential functions; 1.2.2.3. Observations; 1.2.2.4. Decoding strategy; 1.2.3. Results; 1.2.3.1. Zone labelling
1.2.3.2. Text line labelling1.2.3.3. Conclusion; 1.3. Conditional Random Field Models; 1.3.1. Proposed model; 1.3.1.1. Feature functions; 1.3.1.2. Model inference; 1.3.1.3. Parameter learning; 1.3.2. A two level CRF model; 1.3.2.1. Observation features; 1.3.2.2. Label features; 1.3.2.3. Learning; 1.3.3. Integrating more contextual information; 1.3.3.1. Global feature function; 1.3.3.2. Combination of the information sources; 1.3.3.3. Linear combination of the information sources (impl.2); 1.3.3.4. Combination of the information sources using an MLP (impl.3); 1.3.4. Experiments and results 1.4. Conclusions and OutlookAcknowledgments; References; 2. Information Just-in-Time: Going Beyond the Myth of Paperlessness; 2.1. Introduction; 2.2. Information Just-in-Time; 2.2.1. Personal Information Environment; 2.2.2. Hot/Warm/Cold Documents; 2.2.3. Proposed Approach; 2.3. Digital Pen Solution; 2.3.1. Anoto Functionality; 2.3.2. Data Entry Applications; 2.4. iJIT Collaboration Platform; 2.4.1. On-Demand Printing; 2.4.2. Hybrid Document Management System; 2.4.3. Research Notebook Application - iJITNote; 2.4.4. Future Directions; 2.5. Conclusions; Acknowledgments; References 3. The Role of Document Image Analysis in Trustworthy Elections3.1. Introduction; 3.2. History; 3.3. Problems with Current Voting Technologies; 3.4. Experimental Approaches to Reliable Processing of Voting Records; 3.4.1. Statistical distribution of mark sense errors; 3.4.2. Unbiased context-free visual auditing based on ballot images; 3.4.3. Homogenous class display; 3.4.4. Unique identification of ballots; 3.4.5. Error characteristics of DRE with VVPAT; 3.4.6. Development of testing procedures for voting systems; 3.4.7. Affordances for voters with disabilities; 3.5. Some Related Efforts 3.6. Concluding RemarksReferences; 4. Information Retrieval from Document Image Databases; 4.1. Introduction; 4.2. Related Work; 4.3. Word Shape Coding; 4.3.1. Word Shape Coding by Character Stroke Categorization; 4.3.2. Word Shape Coding by Character Boundary Extrema; 4.3.3. Word Shape Coding by Character Holes and Reservoirs; 4.4. Document Image Retrieval; 4.4.1. Document Vector Construction; 4.4.2. Document Similarity Measurement; 4.5. Discussions; 4.5.1. Coding Ambiguity; 4.5.2. Coding Robustness; 4.5.3. Document Similarity Measurements; 4.5.4. Coding Scheme Selection; 4.6. Conclusion References |
| Record Nr. | UNINA-9910790976203321 |
Chaudhuri B. B (Bidyut Baran)
|
||
| New Jersey : , : World Scientific, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in digital document processing and retrieval / / editors, Bidyut Baran Chaudhuri, Swapan Kumar Parui, Indian Statistical Institute, India
| Advances in digital document processing and retrieval / / editors, Bidyut Baran Chaudhuri, Swapan Kumar Parui, Indian Statistical Institute, India |
| Autore | Chaudhuri B. B (Bidyut Baran) |
| Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
| Descrizione fisica | 1 online resource (x, 323 pages) : illustrations |
| Disciplina | 025.04 |
| Collana |
Statistical science and interdisciplinary research
Platinum jubilee series |
| Soggetto topico |
Information storage and retrieval systems
Documentation - Data processing Digital preservation Document imaging systems Electronic publishing Multimedia systems Electronic records |
| ISBN | 981-4368-71-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword; Preface; Contents; 1. Document Image Analysis using Markovian Models: Application to Historical Documents; 1.1. Introduction; 1.2. Hidden Markov Random Field Models; 1.2.1. Theoretical foundations; 1.2.1.1. Simulated annealing; 1.2.1.2. Iterated Conditional Modes (ICM); 1.2.1.3. Highest Confidence First (HCF) algorithm; 1.2.1.4. 2D Dynamic Programming; 1.2.2. Application of MRF labelling to handwritten document segmentation; 1.2.2.1. Probability densities; 1.2.2.2. Clique potential functions; 1.2.2.3. Observations; 1.2.2.4. Decoding strategy; 1.2.3. Results; 1.2.3.1. Zone labelling
1.2.3.2. Text line labelling1.2.3.3. Conclusion; 1.3. Conditional Random Field Models; 1.3.1. Proposed model; 1.3.1.1. Feature functions; 1.3.1.2. Model inference; 1.3.1.3. Parameter learning; 1.3.2. A two level CRF model; 1.3.2.1. Observation features; 1.3.2.2. Label features; 1.3.2.3. Learning; 1.3.3. Integrating more contextual information; 1.3.3.1. Global feature function; 1.3.3.2. Combination of the information sources; 1.3.3.3. Linear combination of the information sources (impl.2); 1.3.3.4. Combination of the information sources using an MLP (impl.3); 1.3.4. Experiments and results 1.4. Conclusions and OutlookAcknowledgments; References; 2. Information Just-in-Time: Going Beyond the Myth of Paperlessness; 2.1. Introduction; 2.2. Information Just-in-Time; 2.2.1. Personal Information Environment; 2.2.2. Hot/Warm/Cold Documents; 2.2.3. Proposed Approach; 2.3. Digital Pen Solution; 2.3.1. Anoto Functionality; 2.3.2. Data Entry Applications; 2.4. iJIT Collaboration Platform; 2.4.1. On-Demand Printing; 2.4.2. Hybrid Document Management System; 2.4.3. Research Notebook Application - iJITNote; 2.4.4. Future Directions; 2.5. Conclusions; Acknowledgments; References 3. The Role of Document Image Analysis in Trustworthy Elections3.1. Introduction; 3.2. History; 3.3. Problems with Current Voting Technologies; 3.4. Experimental Approaches to Reliable Processing of Voting Records; 3.4.1. Statistical distribution of mark sense errors; 3.4.2. Unbiased context-free visual auditing based on ballot images; 3.4.3. Homogenous class display; 3.4.4. Unique identification of ballots; 3.4.5. Error characteristics of DRE with VVPAT; 3.4.6. Development of testing procedures for voting systems; 3.4.7. Affordances for voters with disabilities; 3.5. Some Related Efforts 3.6. Concluding RemarksReferences; 4. Information Retrieval from Document Image Databases; 4.1. Introduction; 4.2. Related Work; 4.3. Word Shape Coding; 4.3.1. Word Shape Coding by Character Stroke Categorization; 4.3.2. Word Shape Coding by Character Boundary Extrema; 4.3.3. Word Shape Coding by Character Holes and Reservoirs; 4.4. Document Image Retrieval; 4.4.1. Document Vector Construction; 4.4.2. Document Similarity Measurement; 4.5. Discussions; 4.5.1. Coding Ambiguity; 4.5.2. Coding Robustness; 4.5.3. Document Similarity Measurements; 4.5.4. Coding Scheme Selection; 4.6. Conclusion References |
| Record Nr. | UNINA-9910813508403321 |
|
Chaudhuri B. B (Bidyut Baran)
|
||
| New Jersey : , : World Scientific, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in digital document processing and retrieval / / editors, Bidyut Baran Chaudhuri (Indian Statistical Institute, India) & Swapan Kumar Parui (Indian Statistical Institute, India)
| Advances in digital document processing and retrieval / / editors, Bidyut Baran Chaudhuri (Indian Statistical Institute, India) & Swapan Kumar Parui (Indian Statistical Institute, India) |
| Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
| Descrizione fisica | 1 online resource (334 p.) |
| Disciplina | 025.04 |
| Altri autori (Persone) |
ChaudhuriB. B (Bidyut Baran)
ParuiSwapan Kumar |
| Collana |
Statistical science and interdisciplinary research
Platinum jubilee series |
| Soggetto topico |
Information storage and retrieval systems
Documentation - Data processing Digital preservation Document imaging systems Electronic publishing Multimedia systems Electronic records |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-4368-71-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword; Preface; Contents; 1. Document Image Analysis using Markovian Models: Application to Historical Documents; 1.1. Introduction; 1.2. Hidden Markov Random Field Models; 1.2.1. Theoretical foundations; 1.2.1.1. Simulated annealing; 1.2.1.2. Iterated Conditional Modes (ICM); 1.2.1.3. Highest Confidence First (HCF) algorithm; 1.2.1.4. 2D Dynamic Programming; 1.2.2. Application of MRF labelling to handwritten document segmentation; 1.2.2.1. Probability densities; 1.2.2.2. Clique potential functions; 1.2.2.3. Observations; 1.2.2.4. Decoding strategy; 1.2.3. Results; 1.2.3.1. Zone labelling
1.2.3.2. Text line labelling1.2.3.3. Conclusion; 1.3. Conditional Random Field Models; 1.3.1. Proposed model; 1.3.1.1. Feature functions; 1.3.1.2. Model inference; 1.3.1.3. Parameter learning; 1.3.2. A two level CRF model; 1.3.2.1. Observation features; 1.3.2.2. Label features; 1.3.2.3. Learning; 1.3.3. Integrating more contextual information; 1.3.3.1. Global feature function; 1.3.3.2. Combination of the information sources; 1.3.3.3. Linear combination of the information sources (impl.2); 1.3.3.4. Combination of the information sources using an MLP (impl.3); 1.3.4. Experiments and results 1.4. Conclusions and OutlookAcknowledgments; References; 2. Information Just-in-Time: Going Beyond the Myth of Paperlessness; 2.1. Introduction; 2.2. Information Just-in-Time; 2.2.1. Personal Information Environment; 2.2.2. Hot/Warm/Cold Documents; 2.2.3. Proposed Approach; 2.3. Digital Pen Solution; 2.3.1. Anoto Functionality; 2.3.2. Data Entry Applications; 2.4. iJIT Collaboration Platform; 2.4.1. On-Demand Printing; 2.4.2. Hybrid Document Management System; 2.4.3. Research Notebook Application - iJITNote; 2.4.4. Future Directions; 2.5. Conclusions; Acknowledgments; References 3. The Role of Document Image Analysis in Trustworthy Elections3.1. Introduction; 3.2. History; 3.3. Problems with Current Voting Technologies; 3.4. Experimental Approaches to Reliable Processing of Voting Records; 3.4.1. Statistical distribution of mark sense errors; 3.4.2. Unbiased context-free visual auditing based on ballot images; 3.4.3. Homogenous class display; 3.4.4. Unique identification of ballots; 3.4.5. Error characteristics of DRE with VVPAT; 3.4.6. Development of testing procedures for voting systems; 3.4.7. Affordances for voters with disabilities; 3.5. Some Related Efforts 3.6. Concluding RemarksReferences; 4. Information Retrieval from Document Image Databases; 4.1. Introduction; 4.2. Related Work; 4.3. Word Shape Coding; 4.3.1. Word Shape Coding by Character Stroke Categorization; 4.3.2. Word Shape Coding by Character Boundary Extrema; 4.3.3. Word Shape Coding by Character Holes and Reservoirs; 4.4. Document Image Retrieval; 4.4.1. Document Vector Construction; 4.4.2. Document Similarity Measurement; 4.5. Discussions; 4.5.1. Coding Ambiguity; 4.5.2. Coding Robustness; 4.5.3. Document Similarity Measurements; 4.5.4. Coding Scheme Selection; 4.6. Conclusion References |
| Record Nr. | UNINA-9910453376903321 |
| New Jersey : , : World Scientific, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimedia information extraction and digital heritage preservation [[electronic resource] /] / editors, Usha Mujoo Munshi, Bidyut Baran Chaudhuri ; series editor, Sankar K. Pal
| Multimedia information extraction and digital heritage preservation [[electronic resource] /] / editors, Usha Mujoo Munshi, Bidyut Baran Chaudhuri ; series editor, Sankar K. Pal |
| Pubbl/distr/stampa | Singapore, : World Scientific, 2011 |
| Descrizione fisica | 1 online resource (413 p.) |
| Disciplina |
006.312
025.84 |
| Altri autori (Persone) |
MunshiUsha Mujoo
ChaudhuriB. B (Bidyut Baran) PalSankar K |
| Collana |
Statistical science and interdisciplinary research
Platinum jubilee series |
| Soggetto topico |
Genealogy
Digital preservation - India |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-23469-6
9786613234698 981-4307-26-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword; Preface; Contents; 1. Motivating Ontology-Driven Information Extraction Burcu Yildiz and Silvia Miksch; Abstract; 1.1 Introduction; 1.2 Information Extraction; 1.3 Related Work; 1.4 Ontology-driven Information Extraction Systems; 1.4.1 System Architecture; 1.4.2 The Ontology Management Module (OMM); 1.4.2.1 Ontology Learning and Population; 1.4.2.2 Ontology Integration; 1.4.2.3 Ontology Evolution; 1.4.3 Rule Generation Module; 1.4.4 The Extraction Module; 1.5 Conclusion and Future Work; References
2. Ontology Based Access of Heritage Artifacts on the Web Santanu Chaudhury and Hiranmay GhoshAbstract; 2.1 Introduction; 2.2 Ontology for Multimedia; 2.3 Construction of Multimedia Ontology; 2.4 Concept Recognition using Multimedia Ontology; 2.5 Distributed Architecture for Digital Heritage Library; 2.6 Application Examples; Heritage; Heritage +; 2.7 Contextual Advertising in Heritage Libraries; 2.8 Conclusion; References; 3. Semantic Integration of Classical and Digital Libraries S. Thaddeus, A. Jeganathan, Gracy T. Leema; Abstract; 3.1 Introduction; 3.2 Motivation 3.3 Overview of Semantic Technology3.4 Resource Ontology; 3.5 Solution Architecture; 3.6 Related Works; 3.7 Conclusion; References; Appendix; 4. Low-level Visual Features with Semantics-based Image Retrieval V.P. Subramanyam Rallabandi; Abstract; 4.1 Introduction; 4.2 General Concepts of Content-Based Image Retrieval; 4.2.1 Query by Picture Example; 4.2.2 Relevance Feedback; 4.2.3 Multi-feature Indexing; 4.2.4 High-level Semantics-based Image Retrieval; 4.3 Proposed Image Retrieval System; 4.3.1 R-Tree Structure SOM; 4.3.2 Self-organizing Relevance Feedback; 4.4 Low-level Visual Descriptors 4.4.1 Color Feature Descriptors4.4.2 Texture Feature Descriptors; 4.4.3 Shape Feature Descriptors; 4.4.4 Iconic Image Analysis; 4.5. Semantic Analysis of Images; 4.5.1 Semantic Reasoning and Contextual Knowledge; 4.5.2 Analysis and Detection; 4.5.3 Reducing the Semantic Gap; 4.5.4 Evaluation of Semantic Reasoning Approach; 4.5.5 Image Retrieval using Semantic Content; 4.6 Experimental Results and Discussion; 4.6.1 Image Database; 4.6.2 Results and Discussion; 4.7 Conclusion; References 5. Narrowing the Semantic Gap in Image Retrieval: A Multimodal Approach William I. Grosky and Rajeev AgrawalAbstract; 5.1 Introduction; 5.2 Multimodal Image Representation and Retrieval; 5.2.1 Representing Image Data; 5.2.2 Taking the Advantage of Modalities; 5.2.3 Modality Fusion Techniques; 5.2.4 Closing the Gap Using Various Image Features; 5.2.5 Approaches to Efficient Image Retrieval; 5.3 Dimensionality Reduction Techniques; 5.3.1 The Curse of Dimensionality; 5.3.1.1 The Problems Caused by High Dimensionality; 5.3.1.2 Overcoming the Curse; 5.3.2 Dimensionality Reduction Techniques 5.4 A Framework for Multimodal-Based Image Retrieval |
| Record Nr. | UNINA-9910464523403321 |
| Singapore, : World Scientific, 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimedia information extraction and digital heritage preservation / / editors, Usha Mujoo Munshi, Bidyut Baran Chaudhuri ; series editor, Sankar K. Pal
| Multimedia information extraction and digital heritage preservation / / editors, Usha Mujoo Munshi, Bidyut Baran Chaudhuri ; series editor, Sankar K. Pal |
| Pubbl/distr/stampa | Singapore : , : World Scientific, , 2011 |
| Descrizione fisica | 1 online resource (413 pages) |
| Disciplina |
006.312
025.84 |
| Altri autori (Persone) |
MunshiUsha Mujoo
ChaudhuriB. B (Bidyut Baran) PalSankar K |
| Collana |
Statistical science and interdisciplinary research
Platinum jubilee series |
| Soggetto topico |
Genealogy
Digital preservation - India |
| ISBN |
1-283-23469-6
9786613234698 981-4307-26-2 |
| Classificazione | 24,1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword; Preface; Contents; 1. Motivating Ontology-Driven Information Extraction Burcu Yildiz and Silvia Miksch; Abstract; 1.1 Introduction; 1.2 Information Extraction; 1.3 Related Work; 1.4 Ontology-driven Information Extraction Systems; 1.4.1 System Architecture; 1.4.2 The Ontology Management Module (OMM); 1.4.2.1 Ontology Learning and Population; 1.4.2.2 Ontology Integration; 1.4.2.3 Ontology Evolution; 1.4.3 Rule Generation Module; 1.4.4 The Extraction Module; 1.5 Conclusion and Future Work; References
2. Ontology Based Access of Heritage Artifacts on the Web Santanu Chaudhury and Hiranmay Ghosh Abstract; 2.1 Introduction; 2.2 Ontology for Multimedia; 2.3 Construction of Multimedia Ontology; 2.4 Concept Recognition using Multimedia Ontology; 2.5 Distributed Architecture for Digital Heritage Library; 2.6 Application Examples; Heritage; Heritage +; 2.7 Contextual Advertising in Heritage Libraries; 2.8 Conclusion; References; 3. Semantic Integration of Classical and Digital Libraries S. Thaddeus, A. Jeganathan, Gracy T. Leema; Abstract; 3.1 Introduction; 3.2 Motivation 3.3 Overview of Semantic Technology 3.4 Resource Ontology; 3.5 Solution Architecture; 3.6 Related Works; 3.7 Conclusion; References; Appendix; 4. Low-level Visual Features with Semantics-based Image Retrieval V.P. Subramanyam Rallabandi; Abstract; 4.1 Introduction; 4.2 General Concepts of Content-Based Image Retrieval; 4.2.1 Query by Picture Example; 4.2.2 Relevance Feedback; 4.2.3 Multi-feature Indexing; 4.2.4 High-level Semantics-based Image Retrieval; 4.3 Proposed Image Retrieval System; 4.3.1 R-Tree Structure SOM; 4.3.2 Self-organizing Relevance Feedback; 4.4 Low-level Visual Descriptors 4.4.1 Color Feature Descriptors4.4.2 Texture Feature Descriptors; 4.4.3 Shape Feature Descriptors; 4.4.4 Iconic Image Analysis; 4.5. Semantic Analysis of Images; 4.5.1 Semantic Reasoning and Contextual Knowledge; 4.5.2 Analysis and Detection; 4.5.3 Reducing the Semantic Gap; 4.5.4 Evaluation of Semantic Reasoning Approach; 4.5.5 Image Retrieval using Semantic Content; 4.6 Experimental Results and Discussion; 4.6.1 Image Database; 4.6.2 Results and Discussion; 4.7 Conclusion; References 5. Narrowing the Semantic Gap in Image Retrieval: A Multimodal Approach William I. Grosky and Rajeev Agrawal Abstract; 5.1 Introduction; 5.2 Multimodal Image Representation and Retrieval; 5.2.1 Representing Image Data; 5.2.2 Taking the Advantage of Modalities; 5.2.3 Modality Fusion Techniques; 5.2.4 Closing the Gap Using Various Image Features; 5.2.5 Approaches to Efficient Image Retrieval; 5.3 Dimensionality Reduction Techniques; 5.3.1 The Curse of Dimensionality; 5.3.1.1 The Problems Caused by High Dimensionality; 5.3.1.2 Overcoming the Curse; 5.3.2 Dimensionality Reduction Techniques 5.4 A Framework for Multimodal-Based Image Retrieval |
| Record Nr. | UNINA-9910788957403321 |
| Singapore : , : World Scientific, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multimedia information extraction and digital heritage preservation / / editors, Usha Mujoo Munshi, Bidyut Baran Chaudhuri ; series editor, Sankar K. Pal
| Multimedia information extraction and digital heritage preservation / / editors, Usha Mujoo Munshi, Bidyut Baran Chaudhuri ; series editor, Sankar K. Pal |
| Pubbl/distr/stampa | Singapore : , : World Scientific, , 2011 |
| Descrizione fisica | 1 online resource (413 pages) |
| Disciplina |
006.312
025.84 |
| Altri autori (Persone) |
MunshiUsha Mujoo
ChaudhuriB. B (Bidyut Baran) PalSankar K |
| Collana |
Statistical science and interdisciplinary research
Platinum jubilee series |
| Soggetto topico |
Genealogy
Digital preservation - India |
| ISBN |
1-283-23469-6
9786613234698 981-4307-26-2 |
| Classificazione | 24,1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Foreword; Preface; Contents; 1. Motivating Ontology-Driven Information Extraction Burcu Yildiz and Silvia Miksch; Abstract; 1.1 Introduction; 1.2 Information Extraction; 1.3 Related Work; 1.4 Ontology-driven Information Extraction Systems; 1.4.1 System Architecture; 1.4.2 The Ontology Management Module (OMM); 1.4.2.1 Ontology Learning and Population; 1.4.2.2 Ontology Integration; 1.4.2.3 Ontology Evolution; 1.4.3 Rule Generation Module; 1.4.4 The Extraction Module; 1.5 Conclusion and Future Work; References
2. Ontology Based Access of Heritage Artifacts on the Web Santanu Chaudhury and Hiranmay Ghosh Abstract; 2.1 Introduction; 2.2 Ontology for Multimedia; 2.3 Construction of Multimedia Ontology; 2.4 Concept Recognition using Multimedia Ontology; 2.5 Distributed Architecture for Digital Heritage Library; 2.6 Application Examples; Heritage; Heritage +; 2.7 Contextual Advertising in Heritage Libraries; 2.8 Conclusion; References; 3. Semantic Integration of Classical and Digital Libraries S. Thaddeus, A. Jeganathan, Gracy T. Leema; Abstract; 3.1 Introduction; 3.2 Motivation 3.3 Overview of Semantic Technology 3.4 Resource Ontology; 3.5 Solution Architecture; 3.6 Related Works; 3.7 Conclusion; References; Appendix; 4. Low-level Visual Features with Semantics-based Image Retrieval V.P. Subramanyam Rallabandi; Abstract; 4.1 Introduction; 4.2 General Concepts of Content-Based Image Retrieval; 4.2.1 Query by Picture Example; 4.2.2 Relevance Feedback; 4.2.3 Multi-feature Indexing; 4.2.4 High-level Semantics-based Image Retrieval; 4.3 Proposed Image Retrieval System; 4.3.1 R-Tree Structure SOM; 4.3.2 Self-organizing Relevance Feedback; 4.4 Low-level Visual Descriptors 4.4.1 Color Feature Descriptors4.4.2 Texture Feature Descriptors; 4.4.3 Shape Feature Descriptors; 4.4.4 Iconic Image Analysis; 4.5. Semantic Analysis of Images; 4.5.1 Semantic Reasoning and Contextual Knowledge; 4.5.2 Analysis and Detection; 4.5.3 Reducing the Semantic Gap; 4.5.4 Evaluation of Semantic Reasoning Approach; 4.5.5 Image Retrieval using Semantic Content; 4.6 Experimental Results and Discussion; 4.6.1 Image Database; 4.6.2 Results and Discussion; 4.7 Conclusion; References 5. Narrowing the Semantic Gap in Image Retrieval: A Multimodal Approach William I. Grosky and Rajeev Agrawal Abstract; 5.1 Introduction; 5.2 Multimodal Image Representation and Retrieval; 5.2.1 Representing Image Data; 5.2.2 Taking the Advantage of Modalities; 5.2.3 Modality Fusion Techniques; 5.2.4 Closing the Gap Using Various Image Features; 5.2.5 Approaches to Efficient Image Retrieval; 5.3 Dimensionality Reduction Techniques; 5.3.1 The Curse of Dimensionality; 5.3.1.1 The Problems Caused by High Dimensionality; 5.3.1.2 Overcoming the Curse; 5.3.2 Dimensionality Reduction Techniques 5.4 A Framework for Multimodal-Based Image Retrieval |
| Record Nr. | UNINA-9910825748103321 |
| Singapore : , : World Scientific, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||