Algorithms and Data Structures : 8th International Workshop, WADS 2003, Ottawa, Ontario, Canada, July 30 - August 1, 2003, Proceedings / / edited by Frank Dehne, Jörg Rüdiger Sack, Michiel Smid

• Record Nr.: UNINA9910144032603321
• Pubbl/distr/stampa: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
• ISBN: 3-540-45078-5
• Edizione: [1st ed. 2003.]
• Descrizione fisica: 1 online resource (XII, 522 p.)
• Collana: Lecture Notes in Computer Science, , 0302-9743 ; ; 2748
• Disciplina: 005.1
• Soggetti: Computer programming; Algorithms; Data structures (Computer science); Numerical analysis; Computer science—Mathematics; Computer graphics; Programming Techniques; Algorithm Analysis and Problem Complexity; Data Structures; Numeric Computing; Discrete Mathematics in Computer Science; Computer Graphics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Multi-party Pseudo-Telepathy -- Adapting (Pseudo)-Triangulations with a Near-Linear Number of Edge Flips -- Shape Segmentation and Matching with Flow Discretization -- Phylogenetic Reconstruction from Gene-Rearrangement Data with Unequal Gene Content -- Toward Optimal Motif Enumeration -- Common-Deadline Lazy Bureaucrat Scheduling Problems -- Bandwidth-Constrained Allocation in Grid Computing -- Algorithms and Approximation Schemes for Minimum Lateness/Tardiness Scheduling with Rejection -- Fast Algorithms for a Class of Temporal Range Queries -- Distribution-Sensitive Binomial ; Queues -- Optimal Worst-Case Operations for Implicit Cache-Oblivious Search Trees -- Extremal Configurations and Levels in Pseudoline Arrangements -- Fast Relative Approximation of Potential Fields -- The One-Round Voronoi Game Replayed -- Integrated Prefetching and Caching with Read and Write Requests -- Online Seat Reservations via Offline Seating Arrangements -- Routing and Call Control Algorithms for Ring Networks -- Algorithms and Models for Railway Optimization -- Approximation of Rectilinear Steiner Trees with Length Restrictions on Obstacles -- Multi-way Space Partitioning Trees -- Cropping-Resilient Segmented Multiple Watermarking -- On Simultaneous Planar Graph Embeddings -- Smoothed Analysis -- Approximation Algorithm for Hotlink Assignments in Web Directories -- Drawing Graphs with Large Vertices and Thick Edges -- Semi-matchings for Bipartite Graphs and Load Balancing -- The Traveling Salesman Problem for Cubic Graphs -- Sorting Circular Permutations by Reversal -- An Improved Bound on Boolean Matrix Multiplication for Highly Clustered Data -- Dynamic Text and Static Pattern Matching -- Real Two Dimensional Scaled Matching -- Proximity Structures for Geometric Graphs -- The Zigzag Path of a Pseudo-Triangulation -- Alternating Paths along Orthogonal Segments -- Improved Approximation Algorithms for the Quality of Service Steiner Tree Problem -- Chips on Wafers -- A Model for Analyzing Black-Box Optimization -- On the Hausdorff Voronoi Diagram of Point Clusters in the Plane -- Output-Sensitive Algorithms for Computing Nearest-Neighbour Decision Boundaries -- Significant-Presence Range Queries in Categorical Data -- Either/Or: Using Vertex Cover Structure in Designing FPT-Algorithms — the Case of k-Internal Spanning Tree -- Parameterized Complexity of Directed Feedback Set Problems in Tournaments -- Compact Visibility Representation and Straight-Line Grid Embedding of Plane Graphs -- New Directions and New Challenges in Algorithm Design and Complexity, Parameterized.
• Sommario/riassunto: The refereed proceedings of the 8th International Workshop on Algorithms and Data Structures, WADS 2003, held in Ottawa, Ontario, Canada, in July/August 2003. The 40 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 126 submissions. A broad variety of current aspects in algorithmics and data structures is addressed.

Artificial Intelligence and Natural Language : 6th Conference, AINL 2017, St. Petersburg, Russia, September 20–23, 2017, Revised Selected Papers / / edited by Andrey Filchenkov, Lidia Pivovarova, Jan Žižka

• Record Nr.: UNINA9910299291103321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
• ISBN: 3-319-71746-4
• Edizione: [1st ed. 2018.]
• Descrizione fisica: 1 online resource (XI, 305 p. 39 illus.)
• Collana: Communications in Computer and Information Science, , 1865-0937 ; ; 789
• Disciplina: 006.3
• Soggetti: Artificial intelligence; Information storage and retrieval systems; Natural language processing (Computer science); Data mining; Computer vision; Artificial Intelligence; Information Storage and Retrieval; Natural Language Processing (NLP); Data Mining and Knowledge Discovery; Computer Vision
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Social Interaction Analysis -- Semantic Feature Aggregation for Gender Identification in Russian Facebook -- 1 Introduction -- 2 Related Work -- 2.1 Feature Aggregation for Author Profiling in Social Media -- 2.2 Topic Modelling -- 2.3 Distributional Clustering -- 3 Dataset -- 4 Feature Aggregation Models -- 4.1 LDA -- 4.2 Author-Topic Model -- 4.3 Distributional Clustering -- 4.4 Automatic Label Assignment -- 5 Author Gender Profiling -- 5.1 Experiment -- 5.2 Results -- 5.3 Correlation Analysis -- 6 Conclusions -- References -- Using Linguistic Activity in Social Networks to Predict and Interpret Dark Psychological Traits -- 1 Introduction -- 2 Method -- 2.1 Psychometrics -- 2.2 Topic Models -- ; 2.3 Predictive Models -- 2.4 Statistical Analysis -- 3 Experiment -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Implementation Details -- 4 Results -- 4.1 Prediction -- 4.2 Statistical Analysis -- 5 Discussion -- 6 Conclusion -- References -- Boosting a Rule-Based Chatbot Using Statistics and User Satisfaction Ratings -- 1 Introduction -- 2 Related Work -- 3 Overview of the Rule-Based Chatbot -- 4 Raw Data and Task Definition -- 4.1 Data -- 4.2 Approach Chosen -- 5 Data Preparation -- 6 Experimental Setup -- 6.1 Data Preprocessing -- 6.2 Baselines -- 6.3 Proposed Systems -- 7 Results and Discussion -- 7.1 System Performance -- 7.2 Difficulty of the Task -- 8 Conclusion and Future Work -- References -- Speech Processing -- Deep Learning for Acoustic Addressee Detection in Spoken Dialogue Systems -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Experimental Data -- 4 Features -- 5 Models -- 6 Results -- 7 Conclusions -- Acknowledgments -- References -- Deep Neural Networks in Russian Speech Recognition -- 1 Introduction -- 2 Related Work -- 3 Architectures of Neural Networks for Acoustic Modeling.; 3.1 LSTM -- 3.2 CNN -- 3.3 ResNet -- 3.4 RCNN -- 4 Datasets -- 4.1 Dataset for the Acoustic Models -- 4.2 Dataset for the Language Model -- 5 Speech Recognition System Implementation -- 6 Experiments and Results -- 6.1 Baseline -- 6.2 MLP -- 6.3 LSTM -- 6.4 CNN -- 6.5 ResNet -- 6.6 RCNN -- 6.7 Comparing of Models -- 6.8 New Model -- 6.9 Summarization -- 7 Conclusion -- References -- Combined Feature Representation for Emotion Classification from Russian Speech -- Abstract -- 1 Introduction and Related Work -- 2 Proposed Method -- 2.1 Feature Extraction -- 2.2 Feature Representation -- 2.3 Classification -- 3 Experimental Settings and Results -- 3.1 RUSLANA Database -- 3.2 Experimental Results -- 4 Conclusion -- Acknowledgments -- References -- Information Extraction -- Active Learning with Adaptive Density Weighted Sampling for Information Extraction from Scientific Papers -- 1 Introduction -- 2 Related Work -- 3 Sampling Strategies for Active Learning -- 4 Task-Independent Features and Classification Pipeline -- 5 Annotation Tool -- 6 Experiments -- 6.1 Data -- 6.2 Evaluation Without Active Learning -- 6.3 Evaluation with Active Learning -- 6.4 Corpus Improvement with Active Learning -- 7 Conclusion -- References -- Application of a Hybrid Bi-LSTM-CRF Model to the Task of Russian Named Entity Recognition -- 1 Introduction -- 2 Neuronal NER Models -- 2.1 Long Short-Term Memory Recurrent Neural Networks -- 2.2 Bi-LSTM -- 2.3 CRF Model for NER Task -- 2.4 Combined Bi-LSTM and CRF Model -- 2.5 Neuro NER Extensions -- 3 Experiments -- 3.1 Datasets -- 3.2 External Word Embedding -- 3.3 Results -- 4 Discussion -- 5 Conclusions -- References -- Web-Scale Data Processing -- Employing Wikipedia Data for Coreference Resolution in Russian -- Abstract -- 1 Introduction -- 2 Related Work on Topic.; 3 Using Semantic Features from Wikipedia Data to Improve Results of Coreference Resolution -- 3.1 Text Preprocessing and Feature Extraction -- 3.2 Adding Wikipedia Data -- 4 Results -- 4.1 Discussion -- 4.2 Future Work -- References -- Building Wordnet for Russian Language from Ru.Wiktionary -- 1 Introduction -- 2 Related Work -- 3 Data -- 4 Algorithm Description -- 4.1 Synonym Relations Extraction -- 4.2 Hierarchical Links Extraction -- 4.3 Links Cleaning -- 5 Results -- 6 Conclusion and Future Work -- References -- Corpus of Syntactic Co-Occurrences: A Delayed Promise -- Abstract -- 1 Online Resources on Word Combinations in Russian -- 2 Method and Used Corpora -- 3 CoSyCo Database and Site -- 4 Evaluation -- 5 Conclusion -- References -- Computation Morphology and Word Embeddings -- A Close Look at Russian Morphological Parsers: Which One Is the Best? -- ; Abstract -- 1 Introduction -- 2 Previous Work -- 3 Russian Morphological Parsers -- 3.1 Mystem -- 3.2 pymorhpy2 -- 3.3 TreeTagger -- 3.4 FreeLing -- 4 Methodology -- 4.1 Corpora -- 4.2 POS Tagsets and Verb Lemmas -- 4.3 Evaluation Measures -- 5 Results and Discussion -- 5.1 Lemmatization -- 5.2 POS Tagging -- 6 Conclusion -- Acknowledgments -- References -- Morpheme Level Word Embedding -- 1 Introduction -- 2 Related Work -- 3 Vocabularies -- 4 Algorithm for Segmentation a Word to Morphemes -- 4.1 Learning -- 4.2 Segmentation -- 5 Morpheme Embedding -- 6 Word Embedding Correction -- 7 Experiments -- 8 Conclusions and Future Work -- References -- Comparison of Vector Space Representations of Documents for the Task of Information Retrieval of Massive Open Online Courses -- 1 Introduction -- 2 Related Work -- 3 Approach to Comparison of Vector Representations -- 3.1 Corpus -- 3.2 Preprocessing -- 3.3 Vector Space Models -- 3.4 Processing Query -- 3.5 Human Judgment -- 3.6 Evaluation Metrics.; 4 Results and Discussion -- 5 Conclusion -- References -- Machine Learning -- Interpretable Probabilistic Embeddings: Bridging the Gap Between Topic Models and Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Probabilistic Word Embeddings -- 4 Additive Regularization and Embeddings for Multiple Modalities -- 5 Experiments -- 6 Conclusions -- References -- Multi-objective Topic Modeling for Exploratory Search in Tech News -- 1 Introduction -- 2 Probabilistic Topic Modeling and Additive Regularization -- 3 Topic-Based Exploratory Search -- 4 Experiments with Topic-Based Search -- 5 Model Parameters Optimization -- 6 Conclusions -- References -- A Deep Forest for Transductive Transfer Learning by Using a Consensus Measure -- 1 Introduction -- 2 Deep Forest -- 3 Consensus Measures and Training the TLDF -- 3.1 Weighted Average of Class Probabilities -- 3.2 The Shannon Entropy as a Consensus Measure -- 4 Convex Measure of the Transfer Learning Consistence -- 5 An Algorithm for the TLDF Training -- 6 Numerical Experiments -- 7 Conclusion -- References -- Russian Paraphrase Detection Shared Task -- ParaPhraser: Russian Paraphrase Corpus and Shared Task -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Paraphrase Extraction and Recognition -- 2.2 Paraphrase Corpora -- 3 The ParaPhraser Project -- 3.1 The Construction Process -- 3.2 Crowdsourcing -- 3.3 Evaluation -- 4 Shared Task -- 4.1 The Task -- 4.2 Baselines -- 4.3 Results -- 4.4 Experiments -- 5 Conclusion -- References -- Effect of Semantic Parsing Depth on the Identification of Paraphrases in Russian Texts -- Abstract -- 1 Introduction -- 2 Parser -- 2.1 The SemSin System -- 2.2 Syntactic Parsing and Semantic Analysis Using SemSin -- 3 Text Analysis -- 3.1 Lemmatization -- 3.2 Semantics. Accounting for Classes -- 3.3 Semantics. Synonymy and Additional Classes -- 3.4 Dependency Tree.; 4 Results -- 5 Conclusion -- References -- RuThes Thesaurus in Detecting Russian Paraphrases -- 1 Introduction -- 2 Related Work -- 3 RuThes Thesaurus -- 4 Using RuThes Synonyms in News Article Clustering -- 5 RuThes in Russian Paraphrasing Task -- 5.1 Russian Paraphrasing Task -- 5.2 Evaluating Thesaurus-Based Features in Paraphrase Detection -- 5.3 Finding the Best Thesaurus Feature -- 5.4 Combining Thesaurus Features with Other Features -- 6 Conclusion -- References -- Knowledge-lean Paraphrase Identification Using Character-Based Features -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Paraphrase Corpora -- 3.1 The Microsoft Paraphrase Corpus -- 3.2 The Plagiarism Detection Corpus -- 3.3 The Twitter Paraphrase Corpus -- 3.4 A Turkish Paraphrase Corpus -- 3.5 A Russian Paraphrase Corpus -- 4 Knowledge-Lean Paraphrase Identification -- ; 4.1 Representing Paraphrase Pairs -- 4.2 Classifier Training -- 4.3 Feature Scaling -- 4.4 Experiments -- 5 Combination of Word- and Character-Based Features -- 6 The Russian Paraphrase Task -- 6.1 Three Class Versus Binary Classification -- 6.2 Results -- 7 Discussion and Conclusions -- Acknowledgements -- References -- Paraphrase Detection Using Machine Translation and Textual Similarity Algorithms -- 1 Introduction -- 1.1 Motivation -- 1.2 Objective -- 1.3 Task Description -- 2 Related Work -- 3 Data Set -- 4 Baseline -- 4.1 Algorithm -- 4.2 Results -- 5 Algorithm -- 5.1 Brief Explanation -- 5.2 Detailed Description -- 5.3 Feature Vector Structure for Each One of the Three Translations -- 6 Comparison of Toolkits on First Task (3-Way Classification) -- 6.1 Results -- 6.2 Confusion Matrix -- 7 Ablation Test and Its Analysis on Second Task (2-Way Classification) -- 7.1 Results -- 7.2 Confusion Matrix -- 7.3 Identifying Best SEMILAR Toolkit Score.; 8 Comparison of Translation Engines for Second Task (2-Way Classification).
• Sommario/riassunto: This book constitutes the refereed proceedings of the 6th Conference on Artificial Intelligence and Natural Language, AINL 2017, held in St. Petersburg, Russia, in September 2017. The 13 revised full papers, 4 revised short papers papers were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on social interaction analysis, speech processing, information extraction, Web-scale data processing, computation morphology and word embedding, machine learning. The volume also contains 6 papers participating in the Russian paraphrase detection shared task.