Computing Semantic Relatedness Using Wikipedia …

A Density-Based Algorithm for Discovering …

A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise Martin Ester, Hans-Peter Kriegel, Jiirg Sander, Xiaowei Xu

  Based, Cluster, Density, Discovering, Algorithm, Density based algorithm for discovering, Density based algorithm for discovering clusters

FastSLAM: A Factored Solution to the Simultaneous ...

FastSLAM: 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-

  Solutions, Tutorials, Simultaneous, Localization, Factored, Simultaneous localization, Fastslam, A factored solution to

Social Roles and their Descriptions

role 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

  Social, Their, Roles, Descriptions, Social roles and their descriptions

Maximum Entropy Inverse Reinforcement Learning

Introduction 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 ...

  Introduction, Learning, Maximum, Reinforcement, Inverse, Entropy, Maximum entropy inverse reinforcement learning

Feature Selection for High-Dimensional Data: A Fast ...

A 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-

  Based, Correlations, Filter, Fast, Fast correlation based filter

PGNet: Real-time Arbitrarily-Shaped Text Spotting with ...

classification, 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

  With, Time, Texts, Recognition, Reasoning, Spatial, Phased, Spotting, Time arbitrarily shaped text spotting with, Arbitrarily

Knowledge-Enhanced Hierarchical Graph Transformer …

ior 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.

  Hierarchical

A Density-Based Algorithm for Discovering Clusters in ...

ters, 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

  Database, Based, Introduction, Cluster, Density, Discovering, Algorithm, Density based algorithm for discovering clusters

Knowledge Discovery and Data Mining: Towards a Unifying ...

cess (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.

  Data, Interested, Mining, Knowledge, Discovery, Knowledge discovery and data mining

Putting Flesh On the Bones: Issues That Arise In Creating …

using 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.

  Composite

CONFLICT AND CONFLICT MANAGEMENT IN …

CONFLICT AND CONFLICT MANAGEMENT IN ORGANIZATIONS: A FRAMEWORK FOR ANALYSIS Jacob Bercovitch Introduction Research into behaviour in organizations can be divided into two

  Analysis, Introduction, Management, Organization, Conflicts, Conflict and conflict management in, Conflict and conflict management in organizations

Parameter estimation for text analysis

Parameter estimation for text analysis Gregor Heinrich Technical Note vsonix GmbH + University of Leipzig, Germany gregor@vsonix.com Abstract. Presents parameter estimation methods common with discrete proba-

  Analysis, Texts, Parameters, Estimation, Parameter estimation for text analysis

About the Speaker Global Initiative of Academics ...

Govt. of India approved a new program titled Global Initiative of Academic Networks (GIAN) in Higher Education aimed at tapping the talent pool of

Language at War: A Critical Discourse Analysis of …

Language at War: A Critical Discourse Analysis of Speeches of Bush and Obama on Terrorism 379 through language, and that ‗one person‘s terrorist is …

  Critical, Analysis, Discourse, Speeches, Critical discourse analysis of, Critical discourse analysis of speeches

2. Differences between maps and images.

2. Differences between maps and images. There are typical differences between maps and images, originating from the distinctions about the aim of data gathering, the acquisition technique, the data processing and the

  Image

Constructing Travel Itineraries from Tagged Geo …

analysis itself. For the latter, a number of other works con-struct and recommend tourist itineraries at various granular-ities [3, 4]. They rely, however, on structured and cleansed

  Form, Analysis, Travel, Constructing, Tagged, Itineraries, Constructing travel itineraries from tagged

arXiv:1301.3781v3 [cs.CL] 7 Sep 2013

Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Google Inc., Mountain View, CA tmikolov@google.com Kai Chen Google Inc., Mountain View, CA