The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Guangquan Zhang - One of the best experts on this subject based on the ideXlab platform.
-
ISKE - Semantic-Based Technology Trend Analysis
2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015Co-Authors: Chao Yang, Guangquan ZhangAbstract:Technology Trend Analysis offers a flexible instrument to understand both opportunity and competition for emerging technologies. Semantic information is used in Science, Technology & Innovation (ST&I) records which makes the technology Trend Analysis more challenging. This paper proposes a semantic-based approach for technology Trend Analysis through emphasizing Subject-Action-Object (SAO) structure, It also applies the Trend Analysis approach to extract technology information and identify and predict the Trend of technology development more effectively. An empirical study on Graphene is completed to demonstrate the proposed Trend Analysis approach.
-
Semantic-Based Technology Trend Analysis
2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015Co-Authors: Chao Yang, Guangquan ZhangAbstract:Technology Trend Analysis offers a flexible instrument to understand both opportunity and competition for emerging technologies. Semantic information is used in Science, Technology & Innovation (ST&I) records which makes the technology Trend Analysis more challenging. This paper proposes a semantic-based approach for technology Trend Analysis through emphasizing Subject-Action-Object (SAO) structure, It also applies the Trend Analysis approach to extract technology information and identify and predict the Trend of technology development more effectively. An empirical study on Graphene is completed to demonstrate the proposed Trend Analysis approach.
Chao Yang - One of the best experts on this subject based on the ideXlab platform.
-
ISKE - Semantic-Based Technology Trend Analysis
2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015Co-Authors: Chao Yang, Guangquan ZhangAbstract:Technology Trend Analysis offers a flexible instrument to understand both opportunity and competition for emerging technologies. Semantic information is used in Science, Technology & Innovation (ST&I) records which makes the technology Trend Analysis more challenging. This paper proposes a semantic-based approach for technology Trend Analysis through emphasizing Subject-Action-Object (SAO) structure, It also applies the Trend Analysis approach to extract technology information and identify and predict the Trend of technology development more effectively. An empirical study on Graphene is completed to demonstrate the proposed Trend Analysis approach.
-
Semantic-Based Technology Trend Analysis
2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015Co-Authors: Chao Yang, Guangquan ZhangAbstract:Technology Trend Analysis offers a flexible instrument to understand both opportunity and competition for emerging technologies. Semantic information is used in Science, Technology & Innovation (ST&I) records which makes the technology Trend Analysis more challenging. This paper proposes a semantic-based approach for technology Trend Analysis through emphasizing Subject-Action-Object (SAO) structure, It also applies the Trend Analysis approach to extract technology information and identify and predict the Trend of technology development more effectively. An empirical study on Graphene is completed to demonstrate the proposed Trend Analysis approach.
Hansaem Park - One of the best experts on this subject based on the ideXlab platform.
-
BigComp - Sentiment Trend Analysis in social web environments
2017 IEEE International Conference on Big Data and Smart Computing (BigComp), 2017Co-Authors: Kyunglag Kwon, Yunwan Jeon, In-jeong Chung, Hansaem ParkAbstract:In this paper, we propose a novel method for sentiment Trend Analysis using Ant Colony Optimization (ACO) algorithm and SentiWordNet. We first collect social data in the form of Resource Description Framework (RDF) triples, and then use ACO algorithm to digitize the amassed RDF triples. Using ACO algorithm, we then compute pheromone values to extract the Trends of the user's sentiments with the modified equations. Next, we compute the user's sentiment scores for the computed pheromone values with respect to the sentiment words with SentiWordNet. Finally, we analyze the sentiment Trend of the online user by time. For verification of the proposed method, we conduct experiments, and compare the analyzed sentiment Trends with their real daily lives. The results show that the proposed method performs satisfactory sentiment Trend Analysis on real data.
-
Sentiment Trend Analysis in social web environments
2017 IEEE International Conference on Big Data and Smart Computing (BigComp), 2017Co-Authors: Kyunglag Kwon, Yunwan Jeon, In-jeong Chung, Hansaem ParkAbstract:In this paper, we propose a novel method for sentiment Trend Analysis using Ant Colony Optimization (ACO) algorithm and SentiWordNet. We first collect social data in the form of Resource Description Framework (RDF) triples, and then use ACO algorithm to digitize the amassed RDF triples. Using ACO algorithm, we then compute pheromone values to extract the Trends of the user's sentiments with the modified equations. Next, we compute the user's sentiment scores for the computed pheromone values with respect to the sentiment words with SentiWordNet. Finally, we analyze the sentiment Trend of the online user by time. For verification of the proposed method, we conduct experiments, and compare the analyzed sentiment Trends with their real daily lives. The results show that the proposed method performs satisfactory sentiment Trend Analysis on real data.
Kyunglag Kwon - One of the best experts on this subject based on the ideXlab platform.
-
BigComp - Sentiment Trend Analysis in social web environments
2017 IEEE International Conference on Big Data and Smart Computing (BigComp), 2017Co-Authors: Kyunglag Kwon, Yunwan Jeon, In-jeong Chung, Hansaem ParkAbstract:In this paper, we propose a novel method for sentiment Trend Analysis using Ant Colony Optimization (ACO) algorithm and SentiWordNet. We first collect social data in the form of Resource Description Framework (RDF) triples, and then use ACO algorithm to digitize the amassed RDF triples. Using ACO algorithm, we then compute pheromone values to extract the Trends of the user's sentiments with the modified equations. Next, we compute the user's sentiment scores for the computed pheromone values with respect to the sentiment words with SentiWordNet. Finally, we analyze the sentiment Trend of the online user by time. For verification of the proposed method, we conduct experiments, and compare the analyzed sentiment Trends with their real daily lives. The results show that the proposed method performs satisfactory sentiment Trend Analysis on real data.
-
Sentiment Trend Analysis in social web environments
2017 IEEE International Conference on Big Data and Smart Computing (BigComp), 2017Co-Authors: Kyunglag Kwon, Yunwan Jeon, In-jeong Chung, Hansaem ParkAbstract:In this paper, we propose a novel method for sentiment Trend Analysis using Ant Colony Optimization (ACO) algorithm and SentiWordNet. We first collect social data in the form of Resource Description Framework (RDF) triples, and then use ACO algorithm to digitize the amassed RDF triples. Using ACO algorithm, we then compute pheromone values to extract the Trends of the user's sentiments with the modified equations. Next, we compute the user's sentiment scores for the computed pheromone values with respect to the sentiment words with SentiWordNet. Finally, we analyze the sentiment Trend of the online user by time. For verification of the proposed method, we conduct experiments, and compare the analyzed sentiment Trends with their real daily lives. The results show that the proposed method performs satisfactory sentiment Trend Analysis on real data.
Eva-maria Jakobs - One of the best experts on this subject based on the ideXlab platform.
-
IPCC - Web comment-based Trend Analysis on deep geothermal energy
IEEE International Professonal Communication 2013 Conference, 2013Co-Authors: Bianka Trevisan, Denise Eraßme, Eva-maria JakobsAbstract:In this paper we present the initial results of a national Trend Analysis - an approach that allows collecting and investigating location- and time-specific acceptance factors from user-generated content. For this purpose, an annotation scheme is adapted that is originally developed for sentiment Analysis and opinion detection. By applying this annotation scheme, German Web comments of a newspaper and a news-site are quantitatively and qualitatively analyzed. The Analysis focuses on the investigation of acceptance drivers of deep geothermal energy. Thereby, it is assumed that the public opinion - positive, negative or neutral - is location-and time-dependent. In contradiction, media often draw an adulterated picture of citizen opinions. Our initial assumption of opposed opinions on deep geothermal energy in public and media was confirmed by the conducted Trend Analysis.
-
Web comment-based Trend Analysis on deep geothermal energy
IEEE International Professonal Communication 2013 Conference, 2013Co-Authors: Bianka Trevisan, Denise Eraßme, Eva-maria JakobsAbstract:In this paper we present the initial results of a national Trend Analysis - an approach that allows collecting and investigating location- and time-specific acceptance factors from user-generated content. For this purpose, an annotation scheme is adapted that is originally developed for sentiment Analysis and opinion detection. By applying this annotation scheme, German Web comments of a newspaper and a news-site are quantitatively and qualitatively analyzed. The Analysis focuses on the investigation of acceptance drivers of deep geothermal energy. Thereby, it is assumed that the public opinion - positive, negative or neutral - is location-and time-dependent. In contradiction, media often draw an adulterated picture of citizen opinions. Our initial assumption of opposed opinions on deep geothermal energy in public and media was confirmed by the conducted Trend Analysis.
