نتایج جستجو برای: classification of text documents

تعداد نتایج: 21200175  

2012
R.

Recent years, feature selection is chief concern in text classification. A major characteristic in text classification is the high dimensionality of the feature space. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the ...

Journal: :Studies in health technology and informatics 2008
Stephan Spat Bruno Cadonna Ivo Rakovac Christian Gütl Hubert Leitner Günther Stark Peter Beck

The amount of narrative clinical text documents stored in Electronic Patient Records (EPR) of Hospital Information Systems is increasing. Physicians spend a lot of time finding relevant patient-related information for medical decision making in these clinical text documents. Thus, efficient and topical retrieval of relevant patient-related information is an important task in an EPR system. This...

2015
Boris A. Galitsky Nina Lebedeva

The problem of classifying text with respect to metalanguage and language object patterns is formulated and its application areas are proposed. Examples of metalanguage patterns in text are foreign language grammar lessons and tutorials on how to write engineering documents. The method targets the text classification tasks where keyword statistics is insufficient do distinguish between such abs...

2007
E. Binaghi

In this paper we describe a new on-line document categorization strategy that can be integrated within Web applications. A salient aspect is the use of neural learning in both representation and classification tasks. Within text documents conceived as images, the regions of interest (RoI) containing information meaningful for categorization are identified with the support of a supervised neural...

Journal: :International Journal of Data Mining & Knowledge Management Process 2014

2015
Xingyuan Chen Yunqing Xia Peng Jin John A. Carroll

Manually labeling documents for training a text classifier is expensive and time-consuming. Moreover, a classifier trained on labeled documents may suffer from overfitting and adaptability problems. Dataless text classification (DLTC) has been proposed as a solution to these problems, since it does not require labeled documents. Previous research in DLTC has used explicit semantic analysis of W...

Journal: :International Journal of Business Intelligence Research 2020

2007
Stephan Spat STEPHAN SPAT

The Steiermärkische Krankenanstalten Ges.m.b.H. (KAGes) conducted the roll-out of an electronic patient record (EPR) system in 2004. This system contains an increasing amount of unstructured clinical text documents in German language. In order to facilitate the patient-related medical decision-making for physicians, this diploma thesis analyses and implements methods retrieving relevant medical...

Journal: :پژوهش های علوم تاریخی 0
حسین بادامچی استادیار گروه تاریخ دانشگاه تهران

writing was invented in late 4th millennium bc in southern mesopotamia and consequently written documents were produced. legal documents are among the most important documents left to us from ancient mesopotamia. sumerian legal documents allow us to study the formation of law in the earliest urban societies. in this paper we study the edicts of uru-ka-gina (also read iri-ka-gina). old and new i...

2006
Zoltán Gyöngyi Hector Garcia-Molina Jan Pedersen

Document categorization is one of the foundational problems in (web) information retrieval. Even though web documents are hyperlinked, most proposed classification techniques take little advantage of the link structure and rely primarily on text features, as it is not immediately clear how to make link information intelligible to supervised machine learning algorithms. This paper introduces a l...

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