نتایج جستجو برای: text document classification
تعداد نتایج: 765658 فیلتر نتایج به سال:
Many text mining applications, especially when investigating Text Classification (TC), require experiments to be performed using common textcollections, such that results can be compared with alternative approaches. With regard to single-label TC, most text-collections (textual data-sources) in their original form have at least one of the following limitations: the overall volume of textual dat...
BACKGROUND Open-source clinical natural-language-processing (NLP) systems have lowered the barrier to the development of effective clinical document classification systems. Clinical natural-language-processing systems annotate the syntax and semantics of clinical text; however, feature extraction and representation for document classification pose technical challenges. METHODS The authors dev...
Bag-of-words representations are used in many NLP applications, such as text classification and sentiment analysis. These representations ignore relations across different sentences in a text and disregard the underlying structure of documents. In this work, we present a method for text classification that takes into account document structure and only considers segments that contain informatio...
This system proposes an efficient text classification approach which is based on multi – layer SVM-NN text classification and two-level representation model. Automated text classification is attractive because it frees organizations from the need of manually organizing document bases, which can be too expensive. This system proposes two-level representation model to represent text data, one is ...
In this paper, we present an innovative method for multi-label text classification. Our method uses Lucene to index texts and then assigns one or more classes to a new text based on its similarity relative to an annotated corpus. For finer granularity, we split the text into phrases, and then we focus on the noun phrases. Instead of classifying the entire text, we classify each noun phrase. The...
Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can be used to define a valid kernel function that takes into account the relations between different terms. Such a kernel is based on the notion of conceptual proximity between pairs of terms, as encoded in the document lattice. W...
In this paper we explore and compare a speech and text classification approach on a corpus of native and non-native English speakers. We experiment on a subset of the International Corpus Network of Asian Learners of English containing the recorded speeches and the equivalent text transcriptions. Our results suggest a high correlation between the spoken and written classification results, showi...
This paper presents an improved graph based k-nn algorithm for text classification. Most of the organization are facing problem of large amount of unorganized data. Most of the existing text classification techniques are based on vector space model which ignores the structural information of the document which is the word order or the co-occurrences of the terms or words. In this paper we have ...
Almost all document analysis approaches need to perform a global analysis of the page orientation as a separate process at an early stage. It would be preferable to estimate the orientation locally after page segmentation and classification, when more knowledge about the different regions is available. In this paper, a novel local skew estimation method is presented that takes advantage of the ...
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