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

Conceptual data modeling for complex applications, such as multimedia and spatiotemporal applications, often results in large, complicated and difficult-to-comprehend diagrams. These diagrams frequently involve repetition of autonomous, semantically meaningful parts that capture similar situations and characteristics. By recognizing such parts and treating them as modeling units, it is possible to simplify the diagrams, as well as the conceptual modeling process. In this paper, based on requirements drawn from real applications, we present a set of modeling units that capture spatial, temporal, and spatiotemporal aspects. To facilitate the conceptual design process, these units are abbreviated in the conceptual diagrams by corresponding spatial, temporal, and spatiotemporal modeling abstractions. The result is more elegant and less-detailed diagrams that are easier to comprehend (for the user) and to construct (for the designer), hut yet semantically rich. An extension of the Entity-Relationship model serves as the context for this study. An example from a real cadastral application illustrates the benefits of using an abstraction-based conceptual model.

Using abstractions for spatio-temporal conceptual modeling

Improved support for modeling information systems involving time-varying, georeferenced information, termed spatio-temporal information, has been a longterm user requirement in a variety of areas, such as cadastral systems that capture the histories of landparcels, routing systems computing possible routes of vehicles, and weather forecasting systems. This chapter concerns the conceptual database design phase for such spatio-temporal information systems and presents two models, namely the spatio-temporal Entity Relationship (ER) Model and the Extended spatio-temporal Unified Modeling Language (UML) as proposed in [33,34] and [26], respectively.

Chapter 3: Conceptual Models for Spatio-temporal Applications

Web objects, often associated with descriptive text documents, are increasingly being geo-tagged. A spatial keyword top-k query retrieves the best k such objects according to a scoring function that considers both spatial distance and textual similarity. However, it is in some cases difficult for users to identify the exact keywords that describe their query intent. After a user issues an initial query and gets back the result, the user may find that some expected objects are missing and may wonder why. Answering the resulting why-not questions can aid users in retrieving better results. However, no existing techniques are able to answer why-not questions by adapting the query keywords. We propose techniques capable of adapting an initial set of query keywords so that expected, but missing, objects enter the result along with other relevant objects. We develop a basic algorithm with a set of optimizations that sequentially examines a sequence of candidate keyword sets. In addition, we present an index-based bound-and-prune algorithm that is able to determine the best sample out of a set of candidates in just one pass of index traversal, thus speeding up the query processing. We also extend the proposed algorithms to handle multiple missing objects. Extensive experimental results offer insight into the efficiency of the proposed techniques in terms of running time and I/O cost.

Answering why-not spatial keyword top-k queries via keyword adaption

Web users and content are increasingly being geo-positioned. This development gives prominence to spatial keyword queries, which involve both the locations and textual descriptions of content. We study the efficient processing of continuously moving top-k spatial keyword (MkSK) queries over spatial text data. State-of-the-art solutions for moving queries employ safe zones that guarantee the validity of reported results as long as the user remains within the safe zone associated with a result. However, existing safe-zone methods focus solely on spatial locations and ignore text relevancy.We propose two algorithms for computing safe zones that guarantee correct results at any time and that aim to optimize the server-side computation as well as the communication between the server and the client. We exploit tight and conservative approximations of safe zones and aggressive computational space pruning. We present techniques that aim to compute the next safe zone efficiently, and we present two types of conservative safe zones that aim to reduce the communication cost. Empirical studies with real data suggest that the proposals are efficient.To understand the effectiveness of the proposed safe zones, we study analytically the expected area of a safe zone, which indicates on average for how long a safe zone remains valid, and we study the expected number of influence objects needed to define a safe zone, which gives an estimate of the average communication cost. The analytical modeling is validated through empirical studies.

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Moving spatial keyword queries: Formulation, methods, and analysis

Migrating applications from conventional to temporal database management technology has received scant mention in the research literature. This paper formally defines three increasingly restrictive notions of upward compatibility which capture properties of a temporal SQL with respect to conventional SQL that, when satisfied, provide for a smooth migration of legacy applications to a temporal system. The notions of upward compatibility dictate the semantics of conventional SQL statements and constrain the semantics of extensions to these statements. The paper evaluates the seven extant temporal extensions to SQL, all of which are shown to complicate migration through design decisions that violate one or more of these notions. We then outline how SQL–92 can be systematically extended to become a temporal query language that satisfies all three notions.

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Christian S. Jensen

Papers

Using abstractions for spatio-temporal conceptual modeling

Chapter 3: Conceptual Models for Spatio-temporal Applications

Answering why-not spatial keyword top-k queries via keyword adaption

Moving spatial keyword queries: Formulation, methods, and analysis

Notions of upward compatibility of temporal query languages