SOMvisua: Data Clustering and Visualization Based on SOM and GHSOM

Text in web pages is based on expert opinion of a large number of people including the views of authors. These views are based on cultural or community aspects, which make extracting information from text very difficult. Search in text usually finds text similarities between paragraphs in documents. This paper proposes a framework for data clustering and visualization called SOMvisua. SOMvisua is based on a graph representation of data input for Self-Organizing Map (SOM) and Growing Hierarchically Self-Organizing Map (GHSOM) algorithms. In SOMvisua, sentences from an input article are represented as graph model instead of vector space model. SOM and GHSOM clustering algorithms construct knowledge from this article

SOMvisua: Data Clustering And Visualization Based on SOM And GHSOM

Text in web pages is based on expert opinion of a large number of people including the views of authors. These views are based on cultural or community aspects which make extracting information from text very difficult. Search in text usually finds text similarities between paragraphs in documents. This paper proposes a framework for data clustering and visualization called SOMvisua. SOMvisua is based on a graph representation of data input for Self-Organizing Map (SOM) and Growing Hierarchically Self-Organizing Map (GHSOM) algorithms. In SOMvisua sentences from an input article are represented as graph model instead of vector space model. SOM and GHSOM clustering algorithms construct knowledge from this article. SOMvisua provides a visual animation for eight famous graph algorithms execution with animation speed control. It also presents six types of visualization. For visualization of similarity lists, we use well-known methods that take a similarity list as input and according to the used similarity measure an adjustable number of most similar sentences are arranged in visual form. In addition, this paper presents a wide variety of text searching. We conducted experiments on the SOMvisua using a large document dataset. Then we compared the performance with that of hierarchal clustering with automated topology based SOM and GHSOM clustering to prove the superiority of SOMvisua

Visualizing text similarities from a graph-based SOM

Text in articles is based on expert opinion of a large number of people including the views of authors. These views are based on cultural or community aspects, which make extracting information from text very difficult. This paper introduced how to utilize the capabilities of a modified graph-based Self-Organizing Map (SOM) in showing text similarities. Text similarities are extracted from an article using Google's PageRank algorithm. Sentences from an input article are represented as graph model instead of vector space model. The resulted graph can be shown in a visual animation for eight famous graph algorithms execution with animation speed control. The resulted graph is used as an input to SOM. SOM clustering algorithm is used to construct knowledge from text data. We used a visual animation for eight famous graph methods with animation speed control and according to similarity measure; an adjustable number of most similar sentences are arranged in visual form. In addition, this paper presents a wide variety of text searching. We had compared our project with famous clustering and visualization project in term of purity, entropy and F measure. Our project showed accepted results and mostly superiority over other projects

The impact of factors of success on the in-house software development for preserving tacit knowledge: survey

Factors of success are aimed to provide knowledge-intensive organisations to better manage their knowledge value. There are multiple ways to capture organization‟ s knowledge and make it available to all their members while it is not easy to capture/share the tacit knowledge among the stakeholders. The purpose of this study was to investigate the impact of factors of success on the in-house software development for preserving tacit knowledge. We conducted a survey to study the impact of these five factors on the tacit knowledge sharing between the developers within the in-house software development environment. This paper is firstly exploring the definition of the knowledge and introducing the types of knowledge those are explicit and tacit knowledge. We discuss the in-house software development concept in which the non-IT organizations may need to develop their own software internally with no need to have a third party software development organization. For tacit knowledge sharing, we considered four factors reviewed in other researches and we added to them the pair programming as a practice. Case study is local bank in Palestine. Based on the results we have, it is confirmed the hypothesis of a positive impact of factors of success on the process of knowledge sharing

تحليل مدونات شبكة التواصل الاجتماعي تويتر خلال حرب 2014 على عزة

The platforms of social Networks play a growing role in influencing the public opinion. In addition, social Networks can describe the reaction of communities towards the reigning conflicts in the world. As a matter of fact, analysis of Social Networks has been used widely for a better understanding how communities address prominent and influential events. As for Twitter, it has used as a platform for exchanging opinions and showing support for either of parties of a conflict. For instance, Twitter witnessed trending of hashtags such as #Gazawar #GazaUnderAttack or #IsraelUnderFire. In this paper, we discuss the role of Social Networks, particularly Twitter, in influencing the Israeli war on Gaza Strip - Palestine during summer 2014. This study shows the mode of public opinion and its reflections on what is trending on Twitter. We construct a dataset drawn from Social Networks sources to examine the behavior of Israeli, Palestinian and foreigner universe. Moreover, we analyze the dataset including tweets as reactions to Gaza War 2014. The results illustrate the important insight of the Social Networks. As regards influencing, it affects perspective of the international universe as well how they address the conflict.The platforms of social Networks play a growing role in influencing the public opinion. In addition, social Networks can describe the reaction of communities towards the reigning conflicts in the world. As a matter of fact, analysis of Social Networks has been used widely for a better understanding how communities address prominent and influential events. As for Twitter, it has used as a platform for exchanging opinions and showing support for either of parties of a conflict. For instance, Twitter witnessed trending of hashtags such as #Gazawar #GazaUnderAttack or #IsraelUnderFire. In this paper, we discuss the role of Social Networks, particularly Twitter, in influencing the Israeli war on Gaza Strip - Palestine during summer 2014. This study shows the mode of public opinion and its reflections on what is trending on Twitter. We construct a dataset drawn from Social Networks sources to examine the behavior of Israeli, Palestinian and foreigner universe. Moreover, we analyze the dataset including tweets as reactions to Gaza War 2014. The results illustrate the important insight of the Social Networks. As regards influencing, it affects perspective of the international universe as well how they address the conflict