Analysis of Images, Social Networks and Texts. 5th International Conference, AIST 2016, Yekaterinburg, Russia, April 7-9, 2016, Revised Selected Papers. Communications in Computer and Information Science
This book constitutes the proceedings of the 5th International Conference on Analysis of Images, Social Networks and Texts, AIST 2016, held in Yekaterinburg, Russia, in April 2016. The 23 full papers, 7 short papers, and 3 industrial papers were carefully reviewed and selected from 142 submissions. The papers are organized in topical sections on machine learning and data analysis; social networks; natural language processing; analysis of images and video.
In this paper we present a comparison of three morphological taggers for Russian with regard to the quality of morphological disambiguation performed by these taggers. We test the quality of the analysis in three different ways: lemmatization, POS-tagging and assigning full morphological tags. We analyze the mistakes made by the taggers, outline their strengths and weaknesses, and present a possible way to improve the quality of morphological analysis for Russian.
Nowadays many algorithms for mobile robot mapping in indoor environments have been created. In this work we use a Kinect 2.0 camera, a visible range cameras Beward B2720 and an infrared camera Flir Tau 2 for building 3D dense maps of indoor environments. We present the RGB-D Mapping and a new fusion algorithm combining visual features and depth information for matching images, aligning of 3D point clouds, a “loop-closure” detection, pose graph optimization to build global consistent 3D maps. Such 3D maps of environments have various applications in robot navigation, real-time tracking, non-cooperative remote surveillance, face recognition, semantic mapping. The performance and computational complexity of the proposed RGB-D Mapping algorithm in real indoor environments is presented and discussed.
Homophily is considered by network scientists as one of the major mechanisms of social network formation. However, the role of dynamic homophily in the network growth process has not been investigated in detail yet. In this paper, we estimate the role of homophily by various attributes at different stages of online network formation process. We consider the process of online friendship formation in the Vkontakte social networking site among first-year students at a Russian university. We reveal that at the beginning of the network formation a similarity in gender and score in entrance exams plays the key role, while by the end of network establishment period the role of the same group affiliation becomes more important. We explain the results with the tendency of students to follow different strategies to control the information flow in their social environment. Do you want to read the rest of this chapter? Homophily Evolution in Online Networks: Who Is a Good Friend and When?.