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## Структура со свойствами тесного мира для решения задачи поиска ближайшего соседа в метрическом пространстве

A novel approach to solving the nearest neighbor search problem in metric space is considered. It is proposed as a data structure to use a graph with navigable small world properties and a gradient descent algorithm as a search algorithm. The problem of the existence of local minima is solved by a series of independent searches. Experimental data are presented to confirm logarithmic complexity of the search algorithm.

We propose a novel approach for solving the approximate nearest neighbor search problem in arbitrary metric spaces. The distinctive feature of our approach is that we can incrementally build a non-hierarchical distributed structure for given metric space data with a logarithmic complexity scaling on the size of the structure and adjustable accuracy probabilistic nearest neighbor queries. The structure is based on a small world graph with vertices corresponding to the stored elements, edges for links between them and the greedy algorithm as base algorithm for searching. Both search and addition algorithms require only local information from the structure. The performed simulation for data in the Euclidian space shows that the structure built using the proposed algorithm has navigable small world properties with logarithmic search complexity at fixed accuracy and has weak (power law) scalability with the dimensionality of the stored data.

This volume contains the papers presented at CS&P 2014: 23th International Workshop on Concurrency, Specification and Programming held on September 28 - October 1, 2014 in Chemnitz. Since the early seventies Warsaw University and Humboldt-University have alternately organized an annual workshop - since 1993 as CS&P. Over time, it has grown from a bilateral seminar to a meeting attended also by colleagues from other countries than Poland and Germany. This year there are 34 participants from 10 countries.

In the course of researching timetabling problems for complex distributed systems this article applies the multi-agent paradigm of computations and presents a correspondent mathematical model for university’s timetabling problem solution. The model takes into account dynamic nature of this problem and individual preferences of different remote users for time and location of classes. In the framework of that model authors propose an original problem-oriented algorithm of multi-agent communication. Developed algorithm is used as a foundation for the distributed software system AgentTime. Based on multi-agent JADE platform AgentTime provides friendly graphical interface for online design of time tables for universities.

Recently similarity graphs became the leading paradigm for efficient nearest neighbor search, outperforming traditional tree-based and LSH-based methods. Similarity graphs perform the search via greedy routing: a query traverses the graph and in each vertex moves to the adjacent vertex that is the closest to this query. In practice, similarity graphs are often susceptible to local minima, when queries do not reach its nearest neighbors, getting stuck in suboptimal vertices. In this paper we propose to learn the routing function that overcomes local minima via incorporating information about the graph global structure. In particular, we augment the vertices of a given graph with additional representations that are learned to provide the optimal routing from the start vertex to the query nearest neighbor. By thorough experiments, we demonstrate that the proposed learnable routing successfully diminishes the local minima problem and significantly improves the overall search performance.

We propose a novel approach to solving the approximate *k*-nearest neighbor search problem in metric spaces. The search structure is based on a navigable small world graph with vertices corresponding to the stored elements, edges to links between them, and a variation of greedy algorithm for searching. The navigable small world is created simply by keeping old Delaunay graph approximation links produced at the start of construction. The approach is very universal, defined in terms of arbitrary metric spaces and at the same time it is very simple. The algorithm handles insertions in the same way as queries: by finding approximate neighbors for the inserted element and connecting it to them. Both search and insertion can be done in parallel requiring only local information from the structure. The structure can be made distributed. The accuracy of the probabilistic k-nearest neighbor queries can be adjusted without rebuilding the structure.

The performed simulation for data in the Euclidean spaces shows that the structure built using the proposed algorithm has small world navigation properties with 2*log*(*n*) insertion and search complexity at fixed accuracy, and performs well at high dimensionality. Simulation on a CoPHiR dataset revealed its high efficiency in case of large datasets (more than an order of magnitude less metric computations at fixed recall) compared to permutation indexes. Only 0.03% of the 10 million 208-dimensional vector dataset is needed to be evaluated to achieve 0.999 recall (virtually exact search). For recall 0.93 processing speed 2800 queries/s can be achieved on a dual Intel X5675 Xenon server node with Java implementation.

This volume contains the papers presented at the 6th International Conference on Similarity Search and Applications (SISAP 2013), held at A Coruna, Spain, during October 2–4, 2013. The International Conference on Similarity Search and Applications (SISAP) is an annual forum for researchers and application developers in the area of similarity data management. It aims at the technological problems shared by many application domains, such as data mining, information retrieval, computer vision, pattern recognition, computational biology, geography, biometrics, machine learning, and many others that need similarity searching as a necessary supporting service. Traditionally, SISAP conferences have put emphasis on the distance-based searching, but in general the conference concerns both the effectiveness and efficiency aspects of any similarity search approach.

Immense volumes of geospatial arrays are generated daily. Examples of such include satellite imagery, numerical simulation, and derivative dataavalanche. Array DBMS are one of the prominent tools for working with large geospatial arrays. Usually the arrays natively come as raster files. ChronosDB is a novel distributed, file based, geospatial array DBMS: chronosdb.gis.land . ChronosDB operates directly on raster files, delegates array processing to existing elaborate command line tools, and outperforms SciDB by up to 75 × on average. This demonstration will showcase three new components of ChronosDB enabling users to interact with the system and appreciate its benefits: (i) a WebGUI (edit, submit queries and get the output), (ii) an execution plan explainer (investigate the generated DAG), and (iii) a dataset visualizer (display ChronosDB arrays on an interactive web map).

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.