Here is the continuation of the comprehensive map of algorithms for extracting patterns from data, with a focus on Natural Language Processing (NLP) and beyond: - Topic Modeling - Latent Dirichlet Allocation (LDA) - Probabilistic Latent Semantic Analysis (PLSA) - Non-Negative Matrix Factorization (NMF) - Hierarchical Dirichlet Process (HDP) - Correlated Topic Model (CTM) - Dynamic Topic Models - Text Classification - Naive Bayes - Logistic Regression - Support Vector Machines (SVM) - Decision Trees and Random Forests - k-Nearest Neighbors (k-NN) - Neural Networks - Convolutional Neural Networks (CNNs) - Recurrent Neural Networks (RNNs) - Attention Mechanisms - Transformers - Sequence Labeling - Hidden Markov Models (HMMs) - Conditional Random Fields (CRFs) - Maximum Entropy Markov Models (MEMMs) - Recurrent Neural Networks (RNNs) - Transformers - Text Summarization - Extractive Summarization - TextRank - LexRank - Latent Semantic Analysis (LSA) - Maximal Marginal Relevance (MMR) - Abstractive Summarization - Sequence-to-Sequence Models - Attention Mechanisms - Pointer-Generator Networks - Transformers - Machine Translation - Statistical Machine Translation (SMT) - Word-Based Models - Phrase-Based Models - Hierarchical Phrase-Based Models - Syntax-Based Models - Neural Machine Translation (NMT) - Sequence-to-Sequence Models - Attention Mechanisms - Transformers - Sentiment Analysis - Lexicon-Based Methods - Dictionary-Based Approaches - Corpus-Based Approaches - Machine Learning Methods - Naive Bayes - Support Vector Machines (SVM) - Logistic Regression - Decision Trees and Random Forests - Deep Learning Methods - Convolutional Neural Networks (CNNs) - Recurrent Neural Networks (RNNs) - Attention Mechanisms - Transformers - Language Modeling - N-gram Models - Unigram Model - Bigram Model - Trigram Model - Neural Language Models - Feedforward Neural Networks - Recurrent Neural Networks (RNNs) - Long Short-Term Memory (LSTM) - Gated Recurrent Units (GRUs) - Transformers (GPT, BERT) - Text Generation - Rule-Based Methods - Statistical Language Models - N-gram Models - Markov Chains - Neural Language Models - Recurrent Neural Networks (RNNs) - Long Short-Term Memory (LSTM) - Gated Recurrent Units (GRUs) - Transformers (GPT) - Information Retrieval - Boolean Models - Vector Space Models - TF-IDF - Okapi BM25 - Probabilistic Models - Binary Independence Model - Probabilistic Relevance Models - Learning to Rank - Pointwise Approaches - Pairwise Approaches - Listwise Approaches - Query Expansion - Pseudo-Relevance Feedback - Thesaurus-Based Expansion - Word Embeddings-Based Expansion - Question Answering - Information Retrieval-Based Methods - Knowledge Base-Based Methods - Machine Reading Comprehension - Attention-Based Models - Transformers (BERT, XLNet, RoBERTa) - Dialogue Systems - Rule-Based Methods - Information Retrieval-Based Methods - Sequence-to-Sequence Models - Hierarchical Reinforcement Learning - Memory Networks - Transformers (GPT, BERT) 7. Graph Analytics - Graph Representation - Adjacency Matrix - Adjacency List - Incidence Matrix - Edge List - Graph Traversal - Breadth-First Search (BFS) - Depth-First Search (DFS) - Shortest Path Algorithms - Dijkstra's Algorithm - Bellman-Ford Algorithm - Floyd-Warshall Algorithm - A* Search - Minimum Spanning Tree - Kruskal's Algorithm - Prim's Algorithm - Network Centrality - Degree Centrality - Eigenvector Centrality - Betweenness Centrality - Closeness Centrality - PageRank - HITS (Hyperlink-Induced Topic Search) - Community Detection - Graph Partitioning - Kernighan-Lin Algorithm - Spectral Partitioning - Hierarchical Clustering - Agglomerative Clustering - Divisive Clustering - Modularity Optimization - Greedy Algorithms - Louvain Algorithm - Stochastic Block Models - Label Propagation Algorithm - Link Prediction - Similarity-Based Methods - Common Neighbors - Jaccard Coefficient - Adamic-Adar Index - Preferential Attachment - Maximum Likelihood Methods - Probabilistic Models - Stochastic Block Models - Latent Space Models - Matrix Factorization - Singular Value Decomposition (SVD) - Non-Negative Matrix Factorization (NMF) - Random Walk-Based Methods - PageRank - SimRank - Random Walk with Restart - Supervised Learning Methods - Feature-Based Methods - Graph Neural Networks (GNNs) - Graph Embedding - Matrix Factorization-Based Methods - Laplacian Eigenmaps - Graph Factorization - Random Walk-Based Methods - DeepWalk - node2vec - Neural Network-Based Methods - Graph Convolutional Networks (GCNs) - GraphSAGE - Graph Attention Networks (GATs) - Graph Autoencoders - Graph Generative Models - Influence Maximization - Greedy Algorithms - Heuristic Algorithms - Reverse Influence Sampling (RIS) - Sketch-Based Methods - Graph Pattern Mining - Frequent Subgraph Mining - Apriori-Based Algorithms - Pattern Growth-Based Algorithms - Significant Subgraph Mining - Discriminative Subgraph Mining - Graph Classification - Kernel-Based Methods - Subgraph-Based Methods - Graph Neural Networks (GNNs) - Graph Matching - Exact Graph Matching - Ullmann's Algorithm - VF2 Algorithm - Inexact Graph Matching - Graph Edit Distance - Maximum Common Subgraph - Graph Kernels - Graph Anonymization - k-Anonymity - l-Diversity - t-Closeness - Differential Privacy - Dynamic Graph Analysis - Temporal Networks - Evolving Networks - Streaming Graphs - Incremental Algorithms - Temporal Motifs - Temporal Community Detection - Temporal Link Prediction - Temporal Node Embedding 8. Spatial and Spatiotemporal Data Analysis - Spatial Data Representation - Raster Data - Vector Data - Tessellations - Regular Tessellations - Irregular Tessellations - Spatial Indexing - Grid-Based Indexing - Quadtree - R-tree - kd-tree - Spatial Statistics - Spatial Autocorrelation - Global Measures (Moran's I, Geary's C) - Local Measures (Local Moran's I, Getis-Ord Gi*) - Spatial Interpolation - Inverse Distance Weighting (IDW) - Kriging (Ordinary, Universal, Indicator) - Spline Interpolation - Nearest Neighbor Interpolation - Spatial Regression - Spatial Lag Model - Spatial Error Model - Geographically Weighted Regression (GWR) - Spatial Clustering - Spatial Scan Statistics - DBSCAN - OPTICS - Hierarchical Clustering - Spatial Outlier Detection - Distance-Based Methods - Density-Based Methods - Neighborhood-Based Methods - Spatial Pattern Analysis - Point Pattern Analysis - Quadrat Analysis - Nearest Neighbor Analysis - Ripley's K-Function - Pair Correlation Function - Polygon Pattern Analysis - Spatial Autocorrelation (Moran's I, Geary's C) - Spatial Heterogeneity (Getis-Ord Gi*) - Network Pattern Analysis - Spatial Interaction Models - Gravity Models - Radiation Models - Spatial Network Analysis - Spatial Modeling - Spatial Interpolation - Deterministic Methods (IDW, Spline) - Geostatistical Methods (Kriging) - Spatial Regression - Linear Regression - Geographically Weighted Regression (GWR) - Spatial Autoregressive Models - Spatial Filtering - Spatial Simulation - Agent-Based Models - Cellular Automata - Spatial Microsimulation - Spatiotemporal Data Analysis - Spatiotemporal Data Representation - Raster Time Series - Vector Time Series - Spatiotemporal Events - Trajectories - Spatiotemporal Statistics - Spatiotemporal Autocorrelation - Spatiotemporal Kriging - Spatiotemporal Regression - Spatiotemporal Pattern Mining - Spatiotemporal Clustering - Spatiotemporal Outlier Detection - Trajectory Pattern Mining - Sequence Pattern Mining - Spatiotemporal Prediction - Spatiotemporal Interpolation - Spatiotemporal Regression - Spatiotemporal Deep Learning - Geovisualization - Cartographic Techniques - Choropleth Maps - Proportional Symbol Maps - Isopleth Maps - Cartograms - Interactive Visualization - Zooming and Panning - Brushing and Linking - Focus+Context - Dynamic Queries - 3D Visualization - Terrain Visualization - City Models - Subsurface Visualization - Animated Maps - Time-Series Animation - Flow Maps - Space-Time Cube 9. Network Science - Network Modeling - Random Graph Models - Erdős–Rényi Model - Watts-Strogatz Model - Barabási–Albert Model - Stochastic Block Model - Generative Models - Preferential Attachment - Copying Model - Fitness Model - Hyperbolic Geometry Model - Network Characterization - Degree Distribution - Path Length and Diameter - Clustering Coefficient - Assortativity - Motifs and Graphlets - Centrality Measures - Degree Centrality - Betweenness Centrality - Closeness Centrality - Eigenvector Centrality - PageRank - HITS (Hyperlink-Induced Topic Search) - Community Detection - Graph Partitioning - Spectral Clustering - Modularity Optimization - Stochastic Block Models - Overlapping Communities - Clique Percolation Method - Link Clustering - BIGCLAM (Cluster Affiliation Model for Big Networks) - Hierarchical Community Structure - Hierarchical Stochastic Block Model - Infomap - Louvain Method - Link Prediction - Similarity-Based Methods - Common Neighbors - Jaccard Coefficient - Adamic-Adar Index - Preferential Attachment - Maximum Likelihood Methods - Probabilistic Models - Stochastic Block Models - Latent Space Models - Matrix Factorization - Singular Value Decomposition (SVD) - Non-Negative Matrix Factorization (NMF) - Random Walk-Based Methods - PageRank - SimRank - Random Walk with Restart - Supervised Learning Methods - Feature-Based Methods - Graph Neural Networks (GNNs) - Epidemic Spreading - Compartmental Models - SIR (Susceptible-Infected-Recovered) Model - SIS (Susceptible-Infected-Susceptible) Model - SEIR (Susceptible-Exposed-Infected-Recovered) Model - Threshold Models - Independent Cascade Model - Linear Threshold Model - Meta-Population Models - Agent-Based Models - Information Cascades - Threshold Models - Granovetter's Model - Watts' Model - Contagion Models - Independent Cascade Model - Linear Threshold Model - Influence Maximization - Greedy Algorithm - Heuristic Methods - Reverse Influence Sampling (RIS) - Network Resilience - Percolation Theory - Robustness Measures - Giant Component Size - Diameter - Efficiency - Cascading Failures - Interdependent Networks - Temporal Networks - Representation and Modeling - Time-Aggregated Graphs - Time-Varying Graphs - Temporal Motifs - Temporal Centrality Measures - Temporal Closeness - Temporal Betweenness - Temporal PageRank - Temporal Community Detection - Estrangement Confinement Method - Multislice Community Detection - Tensor Factorization - Temporal Link Prediction - Time-Series Similarity - Temporal Matrix Factorization - Hawkes Processes - Multilayer Networks - Multiplex Networks - Interdependent Networks - Interconnected Networks - Modeling and Analysis - Tensor Representation - Multilayer Modularity - Multilayer Centrality - Multilayer Community Detection - Multilayer Link Prediction - Higher-Order Interactions - Hypergraphs - Simplicial Complexes - Topological Data Analysis - Persistent Homology - Mapper Algorithm 10. Computational Social Science - Social Network Analysis - Centrality Measures - Degree Centrality - Betweenness Centrality - Closeness Centrality - Eigenvector Centrality - Community Detection - Modularity Optimization - Stochastic Block Models - Clique Percolation Method - Tie Strength Analysis - Embeddedness - Topological Overlap - Dispersion - Homophily and Assortativity - Attribute-Based Assortativity - Structural Assortativity - Influence and Diffusion - Threshold Models - Cascade Models - Influence Maximization - Opinion Dynamics - Voter Model - Majority Rule Model - Bounded Confidence Model - Hegselmann-Krause Model - Axelrod's Model of Cultural Dissemination - Collective Behavior - Herd Behavior - Information Cascades - Collective Decision Making -