Abstract: CNNs automatically extract high-level features from remote sensing (RS) images. PCANet, CCANet, MS-CCANet, and MCCANet are CNN model variants. RS data are often observed from multiple views, but the PCANet is specialized for single-view…
Abstract: Subgraph matching finds all data graph embeddings that match a query graph. Recent algorithms create a tree-structured index on the data graph based on the query graph, order the vertices path-by-path, and enumerate the…
Abstract: We propose Stat-DSM to assess the statistical significance (reliability) of discriminative sub-trajectory mining results. Stat-DSM extracts sub-trajectories that occur statistically significantly more often in one group than the other from two groups of trajectories….
Abstract: Predicting urban traffic is crucial to intelligent transportation systems and public safety, but it is difficult due to three factors: 1) complex spatio-temporal correlations of urban traffic, including spatial correlations between locations and temporal…
Abstract: NER and human community detection use short-text author links. However, challenges await. First, the input short-text contents are noisy, ambiguous, and non-grammatical. Second, traditional text mining methods cannot extract concepts from words and phrases….
Abstract: Human concept learning is semi-supervised learning (SSL) because people naturally combine a few labeled data with lots of unlabeled data to make classification decisions. Human concept learning is both static and dynamic. To accommodate…
Abstract: Location-based data mining has been extensively studied as spatial-temporal trajectory data accumulates. This field studies self-supervised pre-training to learn location embedding vectors. Pre-trained embedding vectors can use abundant unlabeled trajectory data to benefit downstream…
Abstract: Information dissemination mining, ads recommendation, and other applications require early hot event prediction. Existing methods require long-term event observation or expensive feature extraction. Hot and non-hot events have different temporal features, but early data…
Abstract: Geographical topic models are used in recommendations, user mobility modeling, event detection, and geo-tagged document mining for topical region and geographical topics. Studying effective geographical topic models ignores efficiency. However, training geographical topic models…
Abstract: Periodicity is common in temporal social networks. Understanding temporal network group behaviors requires mining periodic communities. Most temporal network community mining studies ignore community periodicity. This paper investigates finding periodic communities in a temporal…
Abstract: A general-purpose, assumption-free imputation method for multivariate missing data, fractional hot-deck imputation (FHDI) fills each missing item with multiple observed values without using artificial values. FHDI J. Im, I. Cho, and J. K. Kim,…
Abstract: Modern traffic management relies on crowd flow prediction (CFP) for many intelligent transportation services tasks. Most methods only forecast metro station entrance and exit flows, which is not enough for traffic management. Managers desperately…
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