In this paper an approach to primary business-media analysis for further information extraction is proposed. We consider business events representation by looking into part of speech (POS) distribution across tagged n-grams. Two Russian business-media corpora, Russian Business Consulting (RBC) and Commersant, are analyzed, and it is shown that they differ not only in style or themes coverage but also in the range of contexts for the words which mark business-events. Purchase, merger and ownership events are given a closer look at, and it is shown that they are mostly represented by noun phrases in both corpora rather than verbal phrases. This paper considers the primary stage of news corpus analysis as part of business events extraction. This stage is closely connected to collocation analysis and aims at extracting key named entities and concepts hierarchy as well as investigating business events' representation. The former is a source of information for the local semantic dictionary whereas the latter may suggest specific ways of further business events extraction including part-of-speech patterns construction. In this paper, two Russian business-media corpora are analyzed and it is shown that they both reveal noun phrases domination in business-events representation. These Russian business-media sources demonstrate difficulties in Information Extraction (IE) imposed by the language (e.g., free word order characterizes Russian in general and especially in the media and in language specific domains). Our corpora analysis is very important for event extraction rules development taking into account the domain and stylistic features of the sources in question.
['Ekaterina V. Pronoza', 'Elena Yagunova']
Business-Media Analysis for Information Extraction