Text line segmentation process represents the key step in the optical character recognition. Hence, the efficiency evaluation procedure for text line segmentation algorithms is the challenge. Text line segmentation process is established by the algorithms application to the text dataset. Furthermore, two goal-oriented methods for the evaluation of the text line segmentation results based on ext...

We describe an experiment into detecting emotions in texts on the Chinese microblog service Sina Weibo (www.weibo.com) using distant supervision via various author-supplied emotion labels (emoticons and smilies). Existing word segmentation tools proved unreliable; better accuracy was achieved using characterbased features. Higher-order n-grams proved to be useful features. Accuracy varied accor...

Most state-of-the-art scene text detection algorithms are deep learning based methods that depend on bounding box regression and perform at least two kinds of predictions: text/nontext classification and location regression. Regression plays a key role in the acquisition of bounding boxes in these methods, but it is not indispensable because text/non-text prediction can also be considered as a ...

Curvilinear text line detection and segmentation in handwritten documents is a significant challenge for handwriting recognition. Given no prior knowledge of script, we model text line detection as an image segmentation problem by enhancing text line structure using a Gaussian window, and adopting the level set method to evolve text line boundaries. Experiments show that the proposed method ach...

The present paper focuses on the segmentation of two-word phrases containing two closely competing lexical hypotheses. It is hypothesized that the bottom-up information, which also includes a mechanism called the Possible-Word Constraint, is explored first in segmenting these phrases. Non-sensory sentential information influences this process at a later stage and only shows an effect if the bot...

In this paper we introduce a dynamic programming algorithm to perform linear text segmentation by global minimization of a segmentation cost function which consists of: (a) within-segment word similarity and (b) prior information about segment length. The evaluation of the segmentation accuracy of the algorithm on Choi's text collection showed that the algorithm achieves the best segmentation a...

In this paper we introduce a dynamic programming algorithm to perform linear text segmentation by global minimization of a segmentation cost function which consists of: (a) within-segment word similarity and (b) prior information about segment length. The evaluation of the segmentation accuracy of the algorithm on a text collection consisting of Greek texts showed that the algorithm achieves hi...

We present a method to leverage radical for learning Chinese character embedding. Radical is a semantic and phonetic component of Chinese character. It plays an important role as characters with the same radical usually have similar semantic meaning and grammatical usage. However, existing Chinese processing algorithms typically regard word or character as the basic unit but ignore the crucial ...

صلاخلا ـ ة : ُّ دعتُ ل ثم ةيعيبطلا تاغللا ةجلاعم تاقيبطت نم ديدعلل ايساسأ انوكم ةيعوضوملا ةئزجتلا قيبطت تامولعملا عاجرتساو صوصنلا صيخلت . نم فدهلا وه ثحبلا اذ ه قت و مي ةيعوضوملا ة ئزجتلا تا يمزراوخ ة يلاعف ضوملا دودحلا ى لع فرعتلا يف ة يبرعلا صوصنلا لخاد ةيعو . م تو قايس لا اذ ه يف ة فلتخم رداصم نم ةيبرع صوصن ةسمخ لخاد اهنوظحلاي يتلا ةركفلا وأ عوضوملا تاريغت ىلع فرعتلل ةيبرعلا ةغللا ءارق نم ة...

Word segmentation is a key problem for Chinese text analysis. In this paper, with the consideration of both word-coverage rate and sentencecoverage rate, based on the classic Bi-Directed Maximum Match (BDMM) segmentation method, a character Directed Graph with ambiguity mark is designed for searching multiple possible segmentation sequences. This method is compared with the classic Maximum Matc...