| Learning approaches: Meta learning, Basic mining techniques: k-means, DBSCAN, SVMs, Naive Bayes, Genetic algorithms, RANSAC, Pattern Recognition, Neural Networks, Spatial & Temporal Mining, Data ambiguity, Multi-label learning, Data Warehouses, Online analytical processing (OLAP), time series, algorithm efficiency, Data pre-processing, visualization, Feature & attributes selection, curse of dimensionality, Deep learning, Advanced clustering schemes, association rules, classification, decision trees, Big Data management, MapReduce, Hadoop, NoSQL, Web mining, Webgraph/directed graphs, pageRank, TrustRank, From Web2.0 to Web3.0: Semantic Web, Linked Data, Link Open Data Cloud, Uncertainty, Fuzziness, Fuzzy Sets, Citation analysis, Advanced knowledge management and representation issues |
