Knowledge Engineering and the Semantic Web. 4th Conference, KESW 2013, St. Petersburg, Russia, October 7-9, 2013. Proceedings
This book constitutes the refereed proceedings of the 4th Conference on Knowledge Engineering and the Semantic Web, KESW 2013, held in St. Petersburg, Russia, in October 2013. The 18 revised full papers presented together with 7 short system descriptions were carefully reviewed and selected from 52 submissions. The papers address research issues related to knowledge representation, semantic web, and linked data.
In the last years native RDF stores made enormous progress in closing the performance gap compared to RDBMS. This albeit smaller gap, however, still prevents adoption of RDF stores in scenarios with high requirements on responsiveness. We try to bridge the gap and present a native RDF store “OntoQuad” and its fundamental design principles. Basing on previous researches, we develop a vector database schema for quadruples, its realization on index data structures, and ways to efficiently implement the joining of two and more data sets simultaneously. We also offer approaches to optimizing the SPARQL query execution plan which is based on its heuristic transformations. The query performance efficiency is checked and proved on BSBM tests. The study results can be taken into consideration during the development of RDF DBMS’s suitable for storing large volumes of Semantic Web data, as well as for the creation of large-scale repositories of semantic data.
By analyzing the logs of corporate e-mail networks we found a number of patterns, showing how the size of ego-networks of individual employees changes on a day by day basis. We proposed a simple model that adequately describes the observed time dependence of an employee's "social circle". Comparison of experimental data with the theoretical model showed that employees are divided into two groups - with fast and slow changes in their social circles, respectively. We believe that the presence of these groups reflects both project-type and process-type of employees' activities. Comparison of data obtained before and during the global economic crisis has shown that the crisis led to an actual reduction in project-type activities.
The paper describes the development of a portal about development and use of tools based on the (meta) modeling (using DSM, DSL, etc.). The architecture of a portal, information retrieval subsystem and document management are described.
The purpose of the portal is the creation of "selfdeveloping" resource, which provides intelligent search and automatic processing of the results (documents and sources), easy navigation on the found resources. Implementation is based on the ontologies approach.
The main feature of suggested methods is an integrated approach to development. The approach bases on a multi-level ontology repository. The portal allows searching and analyzing information, creating and researching model, publishing research results. Software gives an opportunity of a flexible customizing. The main topic of this paper is an intelligent information search means based on semantic indexation, automatic document classification, tracking of semantic links between documents and automatic summarization.
Concept discovery is a Knowledge Discovery in Databases (KDD) research field that uses human-centered techniques such as Formal Concept Analysis (FCA), Biclustering, Triclustering, Conceptual Graphs etc. for gaining insight into the underlying conceptual structure of the data. Traditional machine learning techniques are mainly focusing on structured data whereas most data available resides in unstructured, often textual, form. Compared to traditional data mining techniques, human-centered instruments actively engage the domain expert in the discovery process. This volume contains the contributions to CDUD 2011, the International Workshop on Concept Discovery in Unstructured Data (CDUD) held in Moscow. The main goal of this workshop was to provide a forum for researchers and developers of data mining instruments working on issues with analyzing unstructured data. We are proud that we could welcome 13 valuable contributions to this volume. The majority of the accepted papers described innovative research on data discovery in unstructured texts. Authors worked on issues such as transforming unstructured into structured information by amongst others extracting keywords and opinion words from texts with Natural Language Processing methods. Multiple authors who participated in the workshop used methods from the conceptual structures field including Formal Concept Analysis and Conceptual Graphs. Applications include but are not limited to text mining police reports, sociological definitions, movie reviews, etc.
Proceeding of the 15th International Conference on Artificial Intelligence: Methodology, Systems, Applications , AIMSA 2012, Varna, Bulgaria, September 12-15, 2012.
This paper is an overview of the current issues and tendencies in Computational linguistics. The overview is based on the materials of the conference on computational linguistics COLING’2012. The modern approaches to the traditional NLP domains such as pos-tagging, syntactic parsing, machine translation are discussed. The highlights of automated information extraction, such as fact extraction, opinion mining are also in focus. The main tendency of modern technologies in Computational linguistics is to accumulate the higher level of linguistic analysis (discourse analysis, cognitive modeling) in the models and to combine machine learning technologies with the algorithmic methods on the basis of deep expert linguistic knowledge.
The article discusses the phenomenon of interconnected glocal hospitality communities which have recently spread over the world in the context of the internet development and cultural globalization processes. It focuses on a typical community of users of CouchSurfi ng.org, a major social hospitality network in St. Petersburg. The author argues that, in the framework of this web service, there occurs a transformation of virtual groups of users localized in various spots of the globe into actual interconnected glocal communities which shape shared identities, norms, values, and practices among its members.
There have been implemented engineering and development of multi-agent recommender system «EZSurf» that performs analysis of interests and provides recommendations for the social network «VKontakte» users based on the data from profile of particular user. During the work process different methods and technological solutions have been analyzed with examination of their advantages and disadvantages. Besides of that the comparative analysis of analogous products has been held where the most similar is Russian start-up service - Surfingbird. Based on this analysis the decision of recommender system implementation and integration has been accepted. The feature of this system is that it uses social network “VKontakte” profile for user’s data collection and API of third-party services (LastFM, TheMovieDB) for an extraction of information about similar objects. Such an approach contributes into optimization of recommender system, because it does not require creation of its own object classification system and objects database. The functionality of multi-agent system was separated between three agents. First agent (Collector) collects user data from “VKontakte” profile using VK API. Second agent (Analyzer) collects similar objects from databases of thitd-party services (LastFM, TheMovieDB) that will be the criteria for further search of recommendatory content. For search and selection of information an agent (Recommender) that works as web-crawler has been implemented. System «EZSurf» can be exploited by the users of social network “VKontakte” in everyday life for time economy on web-surfing process. At the same time they will get recommendations on content that are filtered depending on preferences of every particular user.
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
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.