By Mikhail Yu. Khachay, Natalia Konstantinova, Alexander Panchenko, Dmitry Ignatov, Valeri G. Labunets
This e-book constitutes the lawsuits of the Fourth foreign convention on research of pictures, Social Networks and Texts, AIST 2015, held in Yekaterinburg, Russia, in April 2015.
The 24 complete and eight brief papers have been rigorously reviewed and chosen from a hundred and forty submissions. The papers are geared up in topical sections on research of pictures and movies; trend acceptance and laptop studying; social community research; textual content mining and traditional language processing.
Read Online or Download Analysis of Images, Social Networks and Texts: 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9–11, 2015, Revised Selected Papers PDF
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Extra info for Analysis of Images, Social Networks and Texts: 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9–11, 2015, Revised Selected Papers
I develop Normatex1, an open-source Russian text-normalization module, which serves to address this task. This is the ﬁrst open-source system known to the author of such kind. By providing this resource I invite scientists to collaboratively build a high quality text-normalization system. To build a normalization grammar a test parallel corpus was developed. It consists of 66 original texts of the ofﬁcial site of South Ural State University2 and 66 manually preprocessed texts, where all numbers, abbreviations and acronyms were expanded into full words or replaced with pronounceable combination of letters (for example, initials are replaced with the alphabet names of the Russian letters).
As a result, we came up with a list of 37 communities with more than 110, 000 unique members. In order to select particular users with depression propensity, we searched for discussion threads where users claim to be depressed and “on the edge” of suicide. One such thread, started in January 2013, by January 2015 contained about 30, 000 comments from 2550 unique users who shared their personal stories and claims. All those users were selected as our proxy for the target group of people with depression propensity.
The rest of the paper is organized as follows: Sect. 2 briefly presents the classiﬁcation of conventional HOG and PHOG features with the HT-PNN. In Sect. 3, the sequential hierarchical approach is introduced. In Sect. 4, we present the experimental results of the proposed method in the face recognition task . Finally, concluding comments are given in Sect. 5. 2 Classiﬁcation of the PHOG with the HT-PNN Let a training set of R > 1 model images fXr g, r 2 f1; . ; Rg with height Ur and width Vr be speciﬁed.
Analysis of Images, Social Networks and Texts: 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9–11, 2015, Revised Selected Papers by Mikhail Yu. Khachay, Natalia Konstantinova, Alexander Panchenko, Dmitry Ignatov, Valeri G. Labunets