ASPECTS AND MANIFESTATIONS OF MEDIA RELATIONS IN PR PRACTICE (CASE-STUDIES FROM THE AUTOMOTIVE INDUSTRY IN BULGARIA)

The paper reveals, analyses and evaluates the essential characteristics of the relations corporate PR – media in the dynamic environment in Bulgaria. Object of the study are foreign corporations, which bring in their experience in relation to work with the media on the Bulgarian territory. Subject of the study is the relationship between the PR specialists in the corporations and the media, and the role of the communication in the building of their relations. The research thesis is substantiated by the objective location of the place and the significance of the media for the organization activity – good interrelations with the media favor not only the good media performance of the company, but also add a value to the quality of the information, which the journalists spread, in volume, meaning and importance. The theoretical and methodological foundations of the study are based on analyzes and summaries of literary sources in the field of public relations and media theory and practice. An empirical study of cases from the Bulgarian corporate practice of automobile companies was conducted, in order to follow how they work with the media, what are the attitudes of the PR specialists, what are the goals beyond the communication with media. Independent in-depth interviews were conducted with the current PR managers, to explore the qualitative part of media relations, i.e. to survey the demonstrated attitude of the corporations and their PR teams for contact with the media. Of special interest was the so-called uncontrolled means of communication – media publications were gathered, systemized and analyzed. &nbsp

NoTube – making TV a medium for personalized interaction

In this paper, we introduce NoTube’s vision on deploying semantics in interactive TV context in order to contextualize distributed applications and lift them to a new level of service that provides context-dependent and personalized selection of TV content. Additionally, lifting content consumption from a single-user activity to a community-based experience in a connected multi-device environment is central to the project. Main research questions relate to (1) data integration and enrichment - how to achieve unified and simple access to dynamic, growing and distributed multimedia content of diverse formats? (2) user and context modeling - what is an appropriate framework for context modeling, incorporating task-, domain and device-specific viewpoints? (3) context-aware discovery of resources - how could rather fuzzy matchmaking between potentially infinite contexts and available media resources be achieved? (4) collaborative architecture for TV content personalization - how can the combined information about data, context and user be put at disposal of both content providers and end-users in the view of creating extremely personalized services under controlled privacy and security policies? Thus, with the grand challenge in mind - to put the TV viewer back in the driver's seat – we focus on TV content as a medium for personalized interaction between people based on a service architecture that caters for a variety of content metadata, delivery channels and rendering devices

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

TERMS: Text Extraction from Redundant and Multiple Sources

In this work we present our approach to the identity resolution problem: discovering references to one and the same object that come from different sources. Solving this problem is important for a number of different communities (e.g. Database, NLP and Semantic Web) that process heterogeneous data where variations of the same objects are referenced in different formats (e.g. textual documents, web pages, database records, ontologies etc.). Identity resolution aims at creating a single view into the data where different facts are interlinked and incompleteness is remedied. We propose a four-step approach that starts with schema alignment of incoming data sources. As a second step - candidate selection - we discard those entities that are totally different from those that they are compared to. Next the main evidence for identity of two entities comes from applying similarity measures comparing their attribute values. The last step in the identity resolution process is data fusion or merging entities found to be identical into a single object. The principal novel contribution of our solution is the use of a rich semantic knowledge representation that allows for flexible and unified interpretation during the resolution process. Thus we are not restricted in the type of information that can be processed (although we have focussed our work on problems relating to information extracted from text). We report the implementation of these four steps in an IDentity Resolution Framework (IDRF) and their application to two use-cases. We propose a rule based approach for customisation in each step and introduce logical operators and their interpretation during the process. Our final evaluation shows that this approach facilitates high accuracy in resolving identity

MEDIA TRANSPARENCY AND ITS IMPACT ON PR ACTIVITY

This paper analyzes the issue of media transparency and freedom in the Republic of Bulgaria. It concerned particular attention to transparency initiatives both in this country and worldwide, and highlights the greatest role of the media in the democratic society. It draws attention to the specific measures guaranteeing freedom of the media, regulation and selfregulation. It focuses on the impact of media transparency and the transparency of PR activity and their intersection

Focusing on Scenario Recognition in Information Extraction

This paper reports a research effort in Information Extraction, especially in template pattern matching. Our approach uses reach domain knowledge in the football (soccer) area and logical form representation for necessary inferences of facts and templates filling. Our system FRET (Football Reports Extraction Templates) is compatible to the language-engineering environment GATE and handles its internal representations and some intermediate analysis results

Semantically Driven Approach for Scenario Recognition in the IE System FRET

This paper reports a research effort in scenario recognition task in information extraction. The presented approach uses partial semantic analysis based on logical form representation of the templates and the processed text. It is implemented in the system FRET 1 (Football Reports Extraction Templates), which processes specific temporally structured texts. A logical inference mechanism is used for filling template forms. Only scenariorelevant relations between events are linked in the inference chains. The knowledge base plays an important role in this process. Some aspects of negation and modalities that occur in the texts are also taken into account. 1

Ontology-based information extraction for market monitoring and technology watch

Abstract. The h-TechSight Knowledge Management Portal (KMP) enables support for knowledgeintensive industries in monitoring information resources on the Web, as an important factor in business competitiveness. The portal contains tools for identification of concepts and terms from an ontology relevant to the user’s interests, and enables the user to monitor them over time. It also contains tools for ontology management and modification, based on the results of targeted knowledge extraction from the web. The platform provides a means for businesses to keep track of trends and topics of interest in their field, and alert them to changes. In this paper we focus on the tools for targeted search and ontology management, driven by an ontology-based information extraction system, which has been evaluated over a test set of 38 documents and achieves 97 % Precision and 92 % Recall.

natural language technology for information integration in business intelligence

Abstract. Business intelligence requires the collecting and merging of information from many different sources, both structured and unstructured, in order to analyse for example financial risk, operational risk factors, follow trends and perform credit risk management. While traditional data mining tools make use of numerical data and cannot easily be applied to knowledge extracted from free text, traditional information extraction is either not adapted for the financial domain, or does not address the issue of information integration: the merging of information from different kinds of sources. We describe here the development of a system for content mining using domain ontologies, which enables the extraction of relevant information to be fed into models for analysis of financial and operational risk and other business intelligence applications such as company intelligence, by means of the XBRL standard. The results so far are of extremely high quality, due to the implementation of primarily high-precision rules