Google Earth Engine: Planetary-scale geospatial analysis for everyone

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.

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Yago: a core of semantic knowledge

Social Network Analysis

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

The present report is submitted in response to General Assembly resolution 61/106, by which the Assembly adopted the Convention on the Rights of Persons with Disabilities and the Optional Protocol thereto. As requested by the Assembly, a brief overview of the status of the Convention as at 3 August 2007 is presented. The report also contains a brief description of technical arrangements on staff and facilities made necessary for the effective performance of the functions of the Conference of States Parties and the Committee under the Convention and the Optional Protocol, and a description on the progressive implementation of standards and guidelines for the accessibility of facilities and services of the United Nations system. Recent efforts of the United Nations and agencies to disseminate information on the Convention and the Optional Protocol are also described.

わかりやすい障害者の権利条約 : 知的障害のある人の権利のために = Convention on the rights of persons with disabilities

vs. Discrete Modeling. What does it mean to develop a data model with spatio-temporal data types? Actually, this is a design of a many-sorted algebra. There are two steps: 1. Invent a number of types and operations between them that appear to be suitable for querying. So far these are just names, which means one gives a signature. Formally, the signature consists of sorts (names for the types) and operators (names for the operations). 2. Define semantics for this signature, that is, associate an algebra, by defining carrier sets for the sorts and functions for the operators. So the carrier set for a type α contains the possible values for α, and the functions are mappings between the carrier sets. For a formal definition of many-sorted signature and algebra see [24] or [18]. Now one can make such designs at two different levels of abstraction, namely as abstract or as discrete models. Abstract models allow us to make definitions in terms of infinite sets, without worrying whether finite representations of these sets exist. This allows us to view a moving point as a continuous curve in the 3D space, as an arbitrary mapping from an infinite time domain into an also infinite space domain. All the types that we get by application of the type constructor τ are functions over an infinite domain, hence each value is an infinite set. This abstract view is the conceptual model that we are interested in. The curve described by a plane flying over space is continuous; for any point in time there exists a value, regardless of whether we are able to give a finite description for this mapping (or relation). In Section 4.2.2 we have in fact described the types mentioned under this view. In an abstract model, we have no problem in using types like “moving real”, mreal, and operations like mpoint×mpoint → mreal mdistance since it is quite clear that at any time some distance between the moving points exists (when both are defined). 4 Models and Languages: Data Types 105 The only trouble with abstract models is that we cannot store and manipulate them in computers. Only finite and in fact reasonably small sets can be stored; data structures and algorithms have to work with discrete (finite) representations of the infinite point sets. From this point of view, abstract models are entirely unrealistic; only discrete models are usable. This means we somehow need discrete models for moving points and moving regions as well as for all other involved types (mreal, region, . . . ). We can view discrete models as approximations, finite descriptions of the infinite shapes we are interested in. In spatial databases there is the same problem of giving discrete representations for in principle continuous shapes; there almost always linear approximations have been used. Hence, a region is described in terms of polygons and a curve in space (e.g. a river) by a polyline. Linear approximations are attractive because they are easy to handle mathematically; most algorithms in computational geometry work on linear shapes such as rectangles, polyhedra, etc. A linear approximation for a moving point is a polyline in 3D space; a linear approximation for a moving region is a set of polyhedra (see Figure 4.2). Remember that a moving point can be a partial function, hence it may disappear at times, the same is true for the moving region.

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4 Spatio-temporal Models and Languages: An Approach Based on Data Types

Enabling user-generated services could help fuel the mobile revolution. Web sites that enable the sharing of user- generated content such as photos and videos are immensely popular, and their use is on the rise. Technologies that enable Web sites to support the creation, sharing, and deployment of user-generated mobile services could be key factors in the spread of the mobile Internet.

User-Generated Content: The Case for Mobile Services

Research contributions on data modeling, data structures, query processing, and indexing for mobile services may have an impact in the longer term, but each contribution typically offers an isolated solution to one small part of the practical problem of delivering mobile services in the real world. In contrast, this paper describes holistic concepts and techniques for mobile data modeling that are readily applicable in practice. Focus is on services to be delivered to mobile users, such as route guidance, point-of-interest search, road pricing, parking payment, traffic monitoring, etc. While geo-referencing of content is important, it is even more important to relate content to the transportation infrastructure. In addition, several sophisticated, integrated representations of the infrastructure are needed.

Data Modeling for Mobile Services in the Real World

The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important transportation applications. Graph Convolutional Networks (GCNs) are neural networks that are capable of leveraging the structure of a network. However, many implicit assumptions of GCNs do not apply to road networks. We introduce the Relational Fusion Network (RFN), a novel type of GCN designed specifically for road networks. In particular, we propose methods that substantially outperform state-of-the-art GCNs on two machine learning tasks in road networks. Furthermore, we show that state-of-the-art GCNs fail to effectively leverage road network structure on these tasks.

/pdf/graph-convolutional-networks-for-road-networks-4f9bzfw058.pdf

Graph Convolutional Networks for Road Networks

TSQL2 is a declarative query language, and as such, requires a procedural (algebraic) equivalent for implementation. In this chapter, we describe such an algebraic language. We undertook this design in order to show that TSQL2 can be implemented efficiently, with minimal extension of existing techniques.

Christian S. Jensen

Papers

4 Spatio-temporal Models and Languages: An Approach Based on Data Types

User-Generated Content: The Case for Mobile Services

Data Modeling for Mobile Services in the Real World

Graph Convolutional Networks for Road Networks

An Algebra for TSQL2