The Experts below are selected from a list of 749370 Experts worldwide ranked by ideXlab platform
Ioan Roxin - One of the best experts on this subject based on the ideXlab platform.
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Semantic Web-Based Social Media Analysis
Lecture Notes in Computer Science, 2016Co-Authors: Liviu-adrian Cotfas, Camelia Delcea, Antonin Segault, Ioan RoxinAbstract:With the on growing usage of microblogging services, such as Twitter, millions of users share opinions daily on virtually everything. Making sense of this huge amount of data using sentiment and emotion Analysis, can provide invaluable benefits to organizations trying to better understand what the public thinks about their services and products. While the vast majority of now-a-days researches are solely focusing on improving the algorithms used for sentiment and emotion evaluation, the present one underlines the benefits of using a semantic based approach for modeling the Analysis' results, the emotions and the social Media specific concepts. By storing the results as structured data, the possibilities offered by semantic web technologies, such as inference and accessing the vast knowledge in Linked Open Data, can be fully exploited. The paper also presents a novel semantic social Media Analysis platform, which is able to properly emphasize the users' complex feeling such as happiness, affection, surprise, anger or sadness.
Christin Seifert - One of the best experts on this subject based on the ideXlab platform.
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IV - An Application of Edge Bundling Techniques to the Visualization of Media Analysis Results
2010 14th International Conference Information Visualisation, 2010Co-Authors: Wolfgang Kienreich, Christin SeifertAbstract:The advent of consumer-generated and social Media has led to a continuous expansion and diversification of the Media landscape. Media consumers frequently find themselves assuming the role of Media analysts in order to satisfy personal information needs. We propose to employ Knowledge Visualization methods in support of complex Media Analysis tasks. In this paper, we describe an approach which depicts semantic relationships between key political actors using node-link diagrams. Our contribution comprises a force-directed edge bundling algorithm which accounts for semantic properties of edges, a technical evaluation of the algorithm and a report on a real-world application of the approach. The resulting visualization fosters the identification of high-level edge patterns which indicate strong semantic relationships. It has been published by the Austrian Press Agency APA in 2009.
Ludwig Theuvsen - One of the best experts on this subject based on the ideXlab platform.
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Food Chain Actors’ Perceptions of and Adaptations to Volatile Markets: Results of a Media Analysis
2010Co-Authors: Zazie Von Davier, Matthias Heyder, Ludwig TheuvsenAbstract:The volatility of agricultural markets has increased remarkably in recent years. In spite of this, the way in which supply chain actors perceive market volatility has only rarely been analyzed. This paper seeks to close this research gap by presenting empirical findings about how the volatility of agricultural markets is perceived, how increasing market volatilities are being explained, and what adaptations to the volatile external environments are being suggested. Based on a large‐scale Media Analysis, we have identified perceptions, which vary greatly over time, especially with regard to the perception of the threats and opportunities volatility creates for farms and firms and the most frequently identified reasons for volatile prices.
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Media Analysis on Volatile Markets' Dynamics and Adaptive Behavior for the Agri-Food System
International Journal on Food System Dynamics, 2010Co-Authors: Zazie Von Davier, Matthias Heyder, Ludwig TheuvsenAbstract:The volatility of agricultural markets has increased remarkably in recent years. In spite of this, the way in which supply chain actors perceive market volatility has only rarely been analyzed. This paper seeks to close this research gap by presenting empirical findings about how the volatility of agricultural markets is perceived, how increasing market volatilities are being explained, and what adaptations to the volatile external environments are being suggested. Based on a large-scale Media Analysis, we have identified perceptions, which vary greatly over time, especially with regard to the perception of the threats and opportunities volatility creates for farms and firms and the most frequently identified reasons for volatile prices.
Liviu-adrian Cotfas - One of the best experts on this subject based on the ideXlab platform.
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Semantic Web-Based Social Media Analysis
Lecture Notes in Computer Science, 2016Co-Authors: Liviu-adrian Cotfas, Camelia Delcea, Antonin Segault, Ioan RoxinAbstract:With the on growing usage of microblogging services, such as Twitter, millions of users share opinions daily on virtually everything. Making sense of this huge amount of data using sentiment and emotion Analysis, can provide invaluable benefits to organizations trying to better understand what the public thinks about their services and products. While the vast majority of now-a-days researches are solely focusing on improving the algorithms used for sentiment and emotion evaluation, the present one underlines the benefits of using a semantic based approach for modeling the Analysis' results, the emotions and the social Media specific concepts. By storing the results as structured data, the possibilities offered by semantic web technologies, such as inference and accessing the vast knowledge in Linked Open Data, can be fully exploited. The paper also presents a novel semantic social Media Analysis platform, which is able to properly emphasize the users' complex feeling such as happiness, affection, surprise, anger or sadness.
Yonas Demeke Woldemariam - One of the best experts on this subject based on the ideXlab platform.
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SLTU/CCURL@LREC - Adapting Language Specific Components of Cross-Media Analysis Frameworks to Less-Resourced Languages: the Case of Amharic
2020Co-Authors: Yonas Demeke Woldemariam, Adam DahlgrenAbstract:We present an ASR based pipeline for Amharic that orchestrates NLP components within a cross Media Analysis framework (CMAF). One of the major challenges that are inherently associated with CMAFs is effectively addressing multi-lingual issues. As a result, many languages remain under-resourced and fail to leverage out of available Media Analysis solutions. Although spoken natively by over 22 million people and there is an ever-increasing amount of Amharic multiMedia content on the Web, querying them with simple text search is difficult. Searching for, especially audio/video content with simple key words, is even hard as they exist in their raw form. In this study, we introduce a spoken and textual content processing workflow into a CMAF for Amharic. We design an ASR-named entity recognition (NER) pipeline that includes three main components: ASR, a transliterator and NER. We explore various acoustic modeling techniques and develop an OpenNLP-based NER extractor along with a transliterator that interfaces between ASR and NER. The designed ASR-NER pipeline for Amharic promotes the multi-lingual support of CMAFs. Also, the state-of-the art design principles and techniques employed in this study shed light for other less-resourced languages, particularly the Semitic ones.
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Natural language processing in cross-Media Analysis
2018Co-Authors: Yonas Demeke WoldemariamAbstract:A cross-Media Analysis framework is an integrated multi-modal platform where a Media resource containing different types of data such as text, images, audio and video is analyzed with metadata extr ...
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Designing a Speech Recognition-Named Entity Recognition Pipeline for Amharic within a Cross-Media Analysis Framework
2018Co-Authors: Yonas Demeke Woldemariam, Adam DahlgrenAbstract:One of the major challenges that are inherently associated with cross-Media Analysis frameworks, is effectively addressing multilingual issues. As a result, many languages remain under-resourced an ...