Discovering Relations by Entity Search in Lightweight Semantic Text Graphs

Entity search is becoming a popular alternative for full text search. Recently Google released its entity search based on confirmed, human-generated data such as Wikipedia. In spite of these developments, the task of entity discovery, search, or relation search in unstructured text remains a major challenge in the fields of information retrieval and information extraction. This paper tries to address that challenge, focusing specifically on entity relation discovery. This is achieved by processing unstructured text using simple information extraction methods, building lightweight semantic graphs and reusing them for entity relation discovery by applying algorithms from graph theory. An important part is also user interaction with semantic graphs, which can significantly improve information extraction results and entity relation search. Entity relations can be discovered by various text mining methods, but the advantage of the presented method lies in the similarity between the lightweight semantics extracted from a text and the information networks available as structured data. Both graph structures have similar properties and similar relation discovery algorithms can be applied. In addition, we can benefit from the integration of such graph data. We provide both a relevance and performance evaluations of the approach and showcase it in several use case applications

AgentOWL: Semantic Knowledge Model and Agent Architecture

MAS is a powerful paradigm in nowadays distributed systems, however its disadvantage is that it lacks the interconnection with semantic web standards such as OWL. The aim of this article is to present a semantic knowledge model of an agent suitable for discrete environments as well as implementation and a use of such model using the Jena semantic web library and the JADE agent system. The developed library allows interconnection of Agent and Semantic Web technologies can be used in an agent based application where such interconnection is needed. The defined model and methodology show the use of the library in knowledge management applications where the proposed model has been used and evaluated in the scope of the Pellucid and K-Wf Grid IST projects

Ontea: Platform for Pattern Based Automated Semantic Annotation

Automated annotation of web documents is a key challenge of the Semantic Web effort. Semantic metadata can be created manually or using automated annotation or tagging tools. Automated semantic annotation tools with best results are built on various machine learning algorithms which require training sets. Other approach is to use pattern based semantic annotation solutions built on natural language processing, information retrieval or information extraction methods. The paper presents Ontea platform for automated semantic annotation or semantic tagging. Implementation based on regular expression patterns is presented with evaluation of results. Extensible architecture for integrating pattern based approaches is presented. Most of existing semi-automatic annotation solutions can not prove it real usage on large scale data such as web or email communication, but semantic web can be exploited only when computer understandable metadata will reach critical mass. Thus we also present approach to large scale pattern based annotation

Semantic Services Grid in Flood-forecasting Simulations

Flooding in the major river basins of Central Europe is a recurrent event affecting many countries. Almost every year, it takes away lives and causes damage to infrastructure, agricultural and industrial production, and severely affects socio-economic development. Recurring floods of the magnitude and frequency observed in this region is a significant impediment, which requires rapid development of more flexible and effective flood-forecasting systems. In this paper we present design and development of the flood-forecasting system based on the Semantic Grid services. We will highlight the corresponding architecture, discovery and composition of services into workflows and semantic tools supporting the users in evaluating the results of the flood simulations. We will describe in detail the challenges of the flood-forecasting application and corresponding design and development of the service-oriented model, which is based on the well known Web Service Resource Framework (WSRF). Semantic descriptions of the WSRF services will be presented as well as the architecture, which exploits semantics in the discovery and composition of services. Further, we will demonstrate how experience management solutions can help in the process of service discovery and user support. The system provides a unique bottom-up approach in the Semantic Grids by combining the advances of semantic web services and grid architectures

Email Analysis and Information Extraction for Enterprise Benefit

In spite of rapid advances in multimedia and interactive technologies, enterprise users prefer to battle with email spam and overload rather than lose the benefits of communicating, collaborating and solving business tasks over email. Many aspects of email have significantly improved over time, but its overall integration with the enterprise environment remained practically the same. In this paper we describe and evaluate a light-weight approach to enterprise email communication analysis and information extraction. We provide several use cases exploiting the extracted information, such as the enrichment of emails with relevant contextual information, social network extraction and its subsequent search, creation of semantic objects as well as the relationship between email analysis and information extraction on one hand, and email protocols and email servers on the other. The proposed approach was partially tested on several small and medium enterprises (SMEs) and seems to be promising for enterprise interoperability and collaboration in SMEs that depend on emails to accomplish their daily business tasks

Higher order assortativity in complex networks

Assortativity was first introduced by Newman and has been extensively studied and applied to many real world networked systems since then. Assortativity is a graph metrics and describes the tendency of high degree nodes to be directly connected to high degree nodes and low degree nodes to low degree nodes. It can be interpreted as a first order measure of the connection between nodes, i.e. the first autocorrelation of the degree-degree vector. Even though assortativity has been used so extensively, to the author's knowledge, no attempt has been made to extend it theoretically. This is the scope of our paper. We will introduce higher order assortativity by extending the Newman index based on a suitable choice of the matrix driving the connections. Higher order assortativity will be defined for paths, shortest paths, random walks of a given time length, connecting any couple of nodes. The Newman assortativity is achieved for each of these measures when the matrix is the adjacency matrix, or, in other words, the correlation is of order 1. Our higher order assortativity indexes can be used for describing a variety of real networks, help discriminating networks having the same Newman index and may reveal new topological network features.Comment: 24 pages, 16 figure

Ontology and Agent based Approach for Knowledge Management

This dissertation deals with ontology based knowledge representation and its use in multi agent systems. It is well known that knowledge has an immense value in all kinds of businesses and people's every day life. The work presented in this thesis aims to make a stronger connection between knowledge management (KM) and multi-agent systems (MAS), mainly by bringing work done in the semantic web area to MAS. The approach taken is to use ontology based knowledge management in multi agent systems, where uncertain knowledge is not present. This is a suitable model for many applications especially where experience management is needed. The CommonKADS methodology and Protégé ontology editor have been used for knowledge modeling, and the OWL ontology for knowledge representation. The Jena library was used for knowledge and data manipulation and the JADE agent system was used for real implementation o

Browsing Semantic Data in Slovakia

Semantic data browsing is important task for open and governmental data in behalf of public control. There are many projects and solutions regarding semantic data browsing and navigation, but despite the fact, in Slovakia, the availability of such data is poor. It is a shame, because projects like National Action Plan of Open Government and the site data.gov.sk are already operating for several years. In this work we would like to point out key aspects of semantic data and detail the Slovak market of semantic data. We design and propose oursolution of semantic data browsing, evaluate the implementation in our AGECRT NET tool.</p

Motivating intelligent email in business: an investigation into current trends for email processing and communication research

Abstract—According to recent surveys, information workers send and receive an average of 133 messages per day [1], and users talk about “living ” in email, spending an average of 21 percent of their time in the application, as well as reporting general problems with overload. Information created by any business can represent either an asset or a liability, depending largely on how well it is managed. Email is no different in this respect: it can be a highly efficient and useful tool for communication, but only if the information it contains can be managed effectively. One of the main drawbacks of email usage today is its insufficient integration into the collective workspace environment. We believe that by integrating it with other external information (both on the desktop and on distributed servers), one can migrate some of this information to more appropriate storage environments, thereby partly addressing the problem of overload and offering users an integrated access to data and functionality. Currently, there is much research in the area of both personalised and business information management, but very little research that focuses on email as the primary information source, despite its ubiquity. In this paper we survey the current state of the art in email processing and communication research, focusing on the current and potential roles played by email in information management, and commercial and research efforts to integrate a semanticbased approach to email. Keywords-email research; survay; intelligent email I