39,604 research outputs found

    Text Line Segmentation of Historical Documents: a Survey

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    There is a huge amount of historical documents in libraries and in various National Archives that have not been exploited electronically. Although automatic reading of complete pages remains, in most cases, a long-term objective, tasks such as word spotting, text/image alignment, authentication and extraction of specific fields are in use today. For all these tasks, a major step is document segmentation into text lines. Because of the low quality and the complexity of these documents (background noise, artifacts due to aging, interfering lines),automatic text line segmentation remains an open research field. The objective of this paper is to present a survey of existing methods, developed during the last decade, and dedicated to documents of historical interest.Comment: 25 pages, submitted version, To appear in International Journal on Document Analysis and Recognition, On line version available at http://www.springerlink.com/content/k2813176280456k3

    Decomposition of the efficiency of the Chinese state-owned commercial banks at the provincial level

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    This study adopts a bank production function approach to the measurement of banking efficiency at the provincial level in the Chinese state-owned commercial banking sector from 1998 to 2003. Applying Data Envelopment Analysis and efficiency decomposition analysis, this paper has revealed a significant level of pure technical input inefficiency and, to a lesser extent, scale inefficiency across the provincial branches of all the banking groups. The study has also uncovered the extent of inefficiency in individual banking inputs and provincial branches. Finally, the provincial-level efficiency is further decomposed into within-banking-group and between-banking-group effects

    Spartan Daily, November 3, 1965

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    Volume 53, Issue 31https://scholarworks.sjsu.edu/spartandaily/4736/thumbnail.jp

    Spartan Daily, November 3, 1965

    Get PDF
    Volume 53, Issue 31https://scholarworks.sjsu.edu/spartandaily/4736/thumbnail.jp

    Parsing Thai Social Data: A New Challenge for Thai NLP

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    Dependency parsing (DP) is a task that analyzes text for syntactic structure and relationship between words. DP is widely used to improve natural language processing (NLP) applications in many languages such as English. Previous works on DP are generally applicable to formally written languages. However, they do not apply to informal languages such as the ones used in social networks. Therefore, DP has to be researched and explored with such social network data. In this paper, we explore and identify a DP model that is suitable for Thai social network data. After that, we will identify the appropriate linguistic unit as an input. The result showed that, the transition based model called, improve Elkared dependency parser outperform the others at UAS of 81.42%.Comment: 7 Pages, 8 figures, to be published in The 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2019
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