Browsing by Author "Tatar, Serhan"
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Item Open Access Automating information extraction task for Turkish texts(2011) Tatar, SerhanThroughout history, mankind has often suffered from a lack of necessary resources. In today’s information world, the challenge can sometimes be a wealth of resources. That is to say, an excessive amount of information implies the need to find and extract necessary information. Information extraction can be defined as the identification of selected types of entities, relations, facts or events in a set of unstructured text documents in a natural language. The goal of our research is to build a system that automatically locates and extracts information from Turkish unstructured texts. Our study focuses on two basic Information Extraction (IE) tasks: Named Entity Recognition and Entity Relation Detection. Named Entity Recognition, finding named entities (persons, locations, organizations, etc.) located in unstructured texts, is one of the most fundamental IE tasks. Entity Relation Detection task tries to identify relationships between entities mentioned in text documents. Using supervised learning strategy, the developed systems start with a set of examples collected from a training dataset and generate the extraction rules from the given examples by using a carefully designed coverage algorithm. Moreover, several rule filtering and rule refinement techniques are utilized to maximize generalization and accuracy at the same time. In order to obtain accurate generalization, we use several syntactic and semantic features of the text, including: orthographical, contextual, lexical and morphological features. In particular, morphological features of the text are effectively used in this study to increase the extraction performance for Turkish, an agglutinative language. Since the system does not rely on handcrafted rules/patterns, it does not heavily suffer from domain adaptability problem. The results of the conducted experiments show that (1) the developed systems are successfully applicable to the Named Entity Recognition and Entity Relation Detection tasks, and (2) exploiting morphological features can significantly improve the performance of information extraction from Turkish, an agglutinative language.Item Open Access SeaSpider: Automated information gathering on vessel movements in support of marine intelligence, surveillance, and reconnaissance(Spie, 2008-03) Tatar, Serhan; Chapman, D. M. F.SeaSpider is an R&D tool to investigate the development of a software agent that would aid an operator in gathering information about marine vessels from public sources on the Internet. This information would supplement sensor information used for Intelligence, Surveillance, and Reconnaissance (ISR) to enhance Maritime Domain Awareness (MDA) and to complete the Recognized Maritime Picture (RMP). Specifically, SeaSpider is fine-tuned to search for, extract, integrate, and display information about locations (ports), dates and times, and activities (arrival, in berth, departure). One module manages World Wide Web (WWW) searches and retrieves the web pages; another module extracts relevant ship activities, integrates them and populates a database; a third module retrieves information from the database in response to user-generated queries. In this paper, the SeaSpider concept is introduced, the design details of the prototype are presented, and performance is analyzed, with a view towards future research.