Неточные множества для оптимизации SQL-запросов
Today’s data science and business often live apart: IT companies are mired in «burning» projects and do not have enough resources to try out new methods of data analysis. Meanwhile, these new fresh-developed methods are often too crude to be put on stream. Here we present an analytic data processing technology that is based on rough set theory approximations and is shown to be well suited for Big Data analysis.
Proceedings of the 25th International Conference on Database and Expert Systems Applications - DEXA 2014, Munich, Germany, September 1-4, 2014.
This paper investigates the impact of query topology on the difficulty of answering conjunctive queries in the presence of OWL 2 QL ontologies. Our first contribution is to clarify the worst-case size of positive existential (PE), non-recursive Data log (NDL), and first-order (FO) rewritings for various classes of tree-like conjunctive queries, ranging from linear queries to bounded tree width queries. Perhaps our most surprising result is a super polynomial lower bound on the size of PE-rewritings that holds already for linear queries and ontologies of depth 2. More positively, we show that polynomial-size NDL-rewritings always exist for tree-shaped queries with a bounded number of leaves (and arbitrary ontologies), and for bounded tree width queries paired with bounded depth ontologies. For FO-rewritings, we equate the existence of polysize rewritings with well-known problems in Boolean circuit complexity. As our second contribution, we analyze the computational complexity of query answering and establish tractability results (either NL-or LOGCFL-completeness) for a range of query-ontology pairs. Combining our new results with those from the literature yields a complete picture of the succinctness and complexity landscapes for the considered classes of queries and ontologies.
An array DBMS streamlines large N-d array management. A large portion of such arrays originates from the geospatial domain. The arrays often natively come as raster files while standalone command line tools are one of the most popular ways for processing these files. Decades of development and feedback resulted in numerous feature-rich, elaborate, free and quality-assured tools optimized mostly for a single machine. ChronosDB partially delegates in situ data processing to such tools and offers a formal N-d array data model to abstract from the files and the tools. ChronosDB readily provides a rich collection of array operations at scale and outperforms SciDB by up to 75× on average.
Article by R.A. Krupenin, LL.M. (UC Berkeley Law), Lecturer and PhD Candidate at International Laboratory for Information Law and Intellectual Property Law, NRU “HSE,” Member of the Competition Experts Association, Head of Technology, Distribution and M&A Legal Practice Group at Yandex (Moscow, firstname.lastname@example.org), contains analysis of legal nature of search engine results, normative definition of search engines, as well as obligations of search engines to include certain websites into search results.
This volume contains papers presented at the 13th International Conference on Rough Sets, Fuzzy Sets and Granular Computing (RSFDGrC) held during June 25–27, 2011, at the National Research University Higher School of Economics (NRU HSE) in Moscow, Russia. RSFDGrC is a series of scientific events spanning the last 15 years. It investigates the meeting points among the four major disciplines outlined in its title, with respect to both foundations and applications. In 2011, RSFDGrC was co-organized with the 4th International Conference on Pattern Recognition and Machine Intelligence (PReMI), providing a great opportunity for multi-faceted interaction between scientists and practitioners. There were 83 paper submissions from over 20 countries. Each submission was reviewed by at least three Chairs or PC members.We accepted 34 regular papers (41%). In order to stimulate the exchange of research ideas, we also accepted 15 short papers. All 49 papers are distributed among 10 thematic sections of this volume. The conference program featured five invited talks given by Jiawei Han, Vladik Kreinovich, Guoyin Wang, Radim Belohlavek, and C.A. Murthy, as well as two tutorials given by Marcin Szczuka and Richard Jensen. Their corresponding papers and abstracts are gathered in the first two sections of this volume.
This paper comprises papers accepted for presentation at the 14th Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGRC) International Conference which was held as a major part of Joint Rough Set Symposium (JRS 2013) held at Halifax Canada during October 11-14, 2013.
This paper describes an approach for fast ad-hoc analysis of Big Data inside a relational data model. The approach strives to achieve maximal utilization of highly normalized temporary tables through the merge join algorithm. It is designed for the Anchor modeling technique, which requires a very high level of table normalization. Anchor modeling is a novel data warehouse modeling technique, designed for classical databases and adapted by the authors of the article for Big Data environment and a MPP database. Anchor modeling provides flexibility and high speed of data loading, where the presented approach adds support for fast ad-hoc analysis of Big Data sets (tens of terabytes). Different approaches to query plan optimization are described and estimated, for row-based and column-based databases. Theoretical estimations and results of real data experiments carried out in a column-based MPP environment (HP Vertica) are presented and compared. The results show that the approach is particularly favorable when the available RAM resources are scarce, so that a switch is made from pure in-memory processing to spilling over from hard disk, while executing ad-hoc queries. Scaling is also investigated by running the same analysis on different numbers of nodes in the MPP cluster. Configurations of 5, 10 and 12 nodes were tested, using click stream data of Avito, the biggest classified site of Russia.
We present an extension of the ontology-based data access platform Ontop that supports answering SPARQL queries under the OWL 2 QL direct semantics entailment regime for data instances stored in relational databases. On the theoretical side, we show how any input SPARQL query, OWL 2 QL ontology and R2RML mappings can be rewritten to an equivalent SQL query solely over the data. On the practical side, we present initial experimental results demonstrating that by applying the Ontop technologies—the tree-witness query rewriting, T-mapping optimisations using SQL expressivity and database integrity constraints—the system produces scalable SQL queries.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables