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Advanced Data Mining and Applications 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I /
The two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were care...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , , , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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| Edición: | 1st ed. 2013. |
| Colección: | Lecture Notes in Artificial Intelligence,
8346 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 245 | 1 | 0 | |a Advanced Data Mining and Applications |h [electronic resource] : |b 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I / |c edited by Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar Zaiane, Min Yao, Wei Wang. |
| 250 | |a 1st ed. 2013. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2013. | |
| 300 | |a XXII, 588 p. 217 illus. |b online resource. | ||
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| 490 | 1 | |a Lecture Notes in Artificial Intelligence, |x 2945-9141 ; |v 8346 | |
| 505 | 0 | |a Opinion Mining -- Mining E-Commerce Feedback Comments for Dimension Rating Profiles -- Generating Domain-Specific Sentiment Lexicons for Opinion Mining -- Effective Comment Sentence Recognition for Feature-based Opinion Mining -- Exploiting Co-occurrence Opinion Words for Semi-supervised Sentiment Classification -- Behavior Mining -- HN-Sim: A Structural Similarity Measure over Object-Behavior Networks -- Community Based User Behavior Analysis on Daily Mobile Internet Usage -- Stream Mining -- Tracking Drift Types in Changing Data Streams -- Continuously Extracting High-quality Representative Set from Massive Data Streams -- Change Itemset Mining in Data Streams -- Sequential Data Mining -- TKS: Efficient Mining of Top-K Sequential Patterns -- When Optimization is Just an Illusion -- Accurate and fast dynamic time warping -- Online Detecting Spreading Events with the Spatio-temporal Relationship in Water Distribution Networks -- MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns -- Mining Maximal Sequential Patterns without Candidate Maintenance -- Web Mining -- Improved Slope One Collaborative Filtering Predictor Using Fuzzy Clustering -- Towards Building Virtual Vocabularies in the Semantic Web -- Web Mining Accelerated with In-Memory and Column Store Technology -- Image Mining -- Constructing a novel pos-neg manifold for global-based image classification -- 3-D MRI Brain Scan Feature Classification Using an Oct-tree Representation -- Biometric Template Protection Based on Biometric Certificate and Fuzzy Fingerprint Vault -- A Comparative Study of Three Image Representations for Population Estimation Mining Using Remote Sensing Imagery -- Mixed-Norm Regression for Visual Classification -- Research on Map Matching Based on Hidden Markov Model -- Text Mining -- A Rule-Based Named-Entity Recognition for Malay Articles -- Small is Powerful! Towards a Refinedly Enriched Ontology by Careful Pruning and Trimming -- Refine the Corpora Based on Document Manifold -- Social Network Mining -- Online Friends Recommendation based on Geographic Trajectories and Social Relations -- The Spontaneous Behavior in Extreme Events: A Clustering-based Quantitative Analysis -- Restoring: A Greedy Heuristic Approach Based on Neighborhood for Correlation Clustering -- A Local Greedy Search Method for Detecting Community Structure in Weighted Social Networks -- Tree-based Mining for Discovering Patterns of Reposting Behavior in Microblog -- An Improved Parallel Hybrid Seed Expansion (PHSE) Method for Detecting Highly Overlapping Communities in Social Networks -- A Simple Integration of Social Relationship and Text Data for Identifying Potential Customers in Microblogging -- An Energy Model for Network Community Structure Detection -- A Label Propagation-based Algorithm for Community Discovery in Online Social Networks -- Mining Twitter Data for Potential Drug Effects -- Social-Correlation Based Mutual Reinforcement for Short Text Classification and User Interest Tagging -- Classification -- Graph based Feature Augmentation for Short and Sparse Text Classification -- Exploring Deep Belief Nets to Detect and Categorize Chinese Entities -- Extracting Novel Features for E-commerce Page Quality Classification -- Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification -- Predicting Features in Complex 3D Surfaces Using a Point Series Representation: A Case Study in Sheet Metal Forming -- Automatic Labeling of Forums using Bloom's Taxonomy -- Classifying Papers from Different Computer Science Conferences -- Vertex Unique Labelled Subgraph Mining for Vertex Label Classification -- A Similarity-Based Grouping Method for Molecular Docking in Distributed System -- A Bag-of-Tones Model with MFCC Features for Musical Genre Classification -- The GEPSO-Classification Algorithm. | |
| 520 | |a The two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were carefully reviewed and selected from 222 submissions. The papers included in these two volumes cover the following topics: opinion mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification, clustering, association rule mining, pattern mining, regression, predication, feature extraction, identification, privacy preservation, applications, and machine learning. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Information storage and retrieval systems. | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Information Storage and Retrieval. |
| 700 | 1 | |a Motoda, Hiroshi. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Wu, Zhaohui. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Cao, Longbing. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Zaiane, Osmar. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Yao, Min. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Wang, Wei. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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| 776 | 0 | 8 | |i Printed edition: |z 9783642539152 |
| 776 | 0 | 8 | |i Printed edition: |z 9783642539138 |
| 830 | 0 | |a Lecture Notes in Artificial Intelligence, |x 2945-9141 ; |v 8346 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-642-53914-5 |z Texto Completo |
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| 950 | |a Computer Science (SpringerNature-11645) | ||
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