Computing Semantic Relatedness Using Wikipedia …
Computing Semantic Relatedness using Wikipedia-based Explicit Semantic Analysis Evgeniy Gabrilovich and Shaul Markovitch Department of Computer Science
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A Density-Based Algorithm for Discovering …
www.aaai.orgA Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise Martin Ester, Hans-Peter Kriegel, Jiirg Sander, Xiaowei Xu
FastSLAM: A Factored Solution to the Simultaneous ...
www.aaai.orgFastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem ... The problem of simultaneous localization and mapping, also known as SLAM, has attracted immense attention in the mo- ... as a recent tutorial paper [2] documents. Recent research has focused on scal-
Social Roles and their Descriptions
www.aaai.orgrole is defined as “those behaviors characteristic of one or more persons in a context”; i.e., roles focus on a limited set of behaviors that are characteristic of a set of persons and a
Maximum Entropy Inverse Reinforcement Learning
www.aaai.orgIntroduction In problems of imitation learning the goal is to learn to pre-dictthebehavior anddecisionsanagentwouldchoose–e.g., the motions a person would take to grasp an object or the ... Maximum Entropy Inverse Reinforcement Learning ...
Feature Selection for High-Dimensional Data: A Fast ...
www.aaai.orgA Fast Correlation-Based Filter Solution Lei Yu leiyu@asu.edu Huan Liu hliu@asu.edu Department of Computer Science & Engineering, Arizona State University, Tempe, AZ 85287-5406, USA Abstract Feature selection, as a preprocessing step to machine learning, is efiective in reducing di-mensionality, removing irrelevant data, in-
PGNet: Real-time Arbitrarily-Shaped Text Spotting with ...
www.aaai.orgclassification, and action recognition. For example, Zhang et al. (2020) propose a relational reasoning graph network for arbitrary shape text detection by predicting linkages of text components. In this paper, we adopt the Spatial GCN to reasoning the semantic information between point and its
Knowledge-Enhanced Hierarchical Graph Transformer …
www.aaai.orgior hierarchical dependencies and discriminates the type-specific contribution, in forecasting the target behaviors. We apply the proposed KHGT method to three real-world datasets of movie, venue and product recommendations. Experiments show that our model achieves significant gains over 15 state-of-the-art baselines from various lines.
A Density-Based Algorithm for Discovering Clusters in ...
www.aaai.orgters, Efficiency on Large Spatial Databases, Handling Nlj4-275oise. 1. Introduction Numerous applications require the management of spatial data, i.e. data related to space. Spatial Database Systems (SDBS) (Gueting 1994) are database systems for the man-agement of spatial data. Increasingly large amounts of data
Knowledge Discovery and Data Mining: Towards a Unifying ...
www.aaai.orgcess (e.g., the end-user may be more interested in understanding the model than its predictive capa-bilities- see Section 5.2). 7. Data mining: searching for patterns of interest in a particular representational form or a set of such rep-resentations: classification rules or trees, regression, clustering, and so forth.
Putting Flesh On the Bones: Issues That Arise In Creating …
www.aaai.orgusing composite, informative functional designators rather than simple names: (Nth (The (LeftFn FingerSeries)) means the fourth digit of the left-hand finger series counting laterally from the thumb. The composite description with nested functions allows the Cyc program to draw various fairly general inferences automatically.
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