In the classical information retrieval IR problem the system must nd all docu ments in a collection that are related to a topic de ned by a user s query A common approach to the IR problem is to represent documents and the query as vectors of term frequencies and rank the documents in the collection according to their inner product similarity with respect to the query When a sample of evaluated...

The article focuses on a rather unexplored topic in NLP: parenthetical classification. Parentheticals are defined as any text sequence between parentheses. They have been approached from isolated perspectives, like translation pairs extraction, but a full account of their syntactic and semantic properties is lacking. This article proposes a new comprehensive scheme drawn from corpus-based lingu...

In this paper we present an application of information extraction technologies to data mining. The system has the goal of producing reliable reports on opinions that customers express about companies and/or products. Information extraction is regarded as an enabling technology by which structured databases can be populated from unstructured texts available on the web. The approach can be consid...

Information extraction and text classification are usually seen as complementary forms of shallow text processing, in that they are aimed at very different tasks. In this paper, we describe two simple but real-world domains in which text classification techniques can be used directly for information extraction. Specifically, we describe systems for extracting information from business cards, an...

Background: In order to check the practicality of classification of Universities of Medical Sciences (UMSs) based on their infrastructures, and scientific contributions, this study explored the most appropriate indicators to measure the size and productivity of UMSs. Methods: In the first phase, we approached a group of experts who had a deep experience in the management of UMSs and in the mini...

The right and left hand Motor Imagery (MI) analysis based on the electroencephalogram (EEG) signal can directly link the central nervous system to a computer or a device. This study aims to identify a set of robust and nonlinear effective brain connectivity features quantified by transfer entropy (TE) to characterize the relationship between brain regions from EEG signals and create a hierarchi...

with the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. one of the major problems in text classification relates to the high dimensional feature spaces. therefore, the main goal of text classification is to reduce the dimensionality of features space. there are many feature selection methods. however...