2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)最新文献_第4页

Applications of artificial intelligence control for Parallel Discrete-Manipulators 人工智能在并联离散机械臂控制中的应用

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803114

Felix Pasila, Roche Alimin

引用次数: 4

Query subtopic diversification based on cluster ranking and semantic features 基于聚类排序和语义特征的子主题多样化查询

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803099

Md Shajalal, Md. Zia Ullah, Abu Nowshed Chy, Masaki Aono

{"title":"Query subtopic diversification based on cluster ranking and semantic features","authors":"Md Shajalal, Md. Zia Ullah, Abu Nowshed Chy, Masaki Aono","doi":"10.1109/ICAICTA.2016.7803099","DOIUrl":"https://doi.org/10.1109/ICAICTA.2016.7803099","url":null,"abstract":"Search queries are usually short, ambiguous, and have multiple interpretations. Identifying possible subtopics is one of the key strategy to disambiguate a search query. In recent years, researchers have investigated subtopic mining through a variety of approaches. This paper is aimed at mining a diversified list of subtopics underlying a query. In our approach, first, we apply soft clustering to the subtopic candidates based on frequent phrases to group subtopics of similar intents. Second, we introduce multiple semantic features to rank subtopics in the cluster. The clusters are then diversified by balancing relevancy and novelty. The cluster relevance score is estimated by combining cluster score and subtopic importance. We employ Jaccard coefficient to estimate the novelty of a cluster based on word embedding. Finally, a diversified list of subtopics is generated by selecting top ranked subtopic from each cluster. We conducted experiments on NTCIR-10 INTENT-2 and NTCIR-12 IMINE-2 English subtopic mining test collections. The results conclude that our proposed method outperforms other methods in subtopic mining.","PeriodicalId":367414,"journal":{"name":"2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117081152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Development of multimedia streaming technology over bandwidth-limited network and its implementation in rural area 基于有限带宽网络的多媒体流媒体技术的发展及其在农村地区的实现

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803140

Y. Bandung, Harry Chandra Tanuwidjaja, L. B. Subekti

{"title":"Development of multimedia streaming technology over bandwidth-limited network and its implementation in rural area","authors":"Y. Bandung, Harry Chandra Tanuwidjaja, L. B. Subekti","doi":"10.1109/ICAICTA.2016.7803140","DOIUrl":"https://doi.org/10.1109/ICAICTA.2016.7803140","url":null,"abstract":"There is a big difference between the development of rural area and city area in Indonesia. Education level in the countryside is far less superior to town life. In order to address that problem, information and communication technology (ICT) will be used. Multimedia streaming technology is a solution to enhance the quality of life in rural area. However, the development of Internet network infrastructure in countryside is still not as good as in big cities. As a result, the people in countryside faced instability network problem. This situation is called bandwidth limited network, a condition which is caused by the up and down of Internet speed. Because of that, a multimedia streaming technology which can be operated over bandwidth-limited network is developed. In this paper, we present the development of multimedia streaming technology and its application in rural area of Indonesia. Specifically, we investigated about the performance of the multimedia streaming technology using eighteen parameters, focusing in audio-video delay, jitter, and jitter buffer. The result showed that the average video delay when there was no Internet problem was under 1 second, captured jitter average was at 3 ms, jitter buffer was under 1 second, and total bandwidth was far under 3.9 Mbps. As a result, the multimedia streaming technology is very suitable to be implemented in bandwidth limited network to enhance the quality of education in rural area of Indonesia.","PeriodicalId":367414,"journal":{"name":"2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130793010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Predicting football match results with logistic regression 用逻辑回归预测足球比赛结果

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803111

Darwin Prasetio, Dra. Harlili

{"title":"Predicting football match results with logistic regression","authors":"Darwin Prasetio, Dra. Harlili","doi":"10.1109/ICAICTA.2016.7803111","DOIUrl":"https://doi.org/10.1109/ICAICTA.2016.7803111","url":null,"abstract":"Many efforts has been made in order to predict football matches result and selecting significant variables in football. Prediction is very useful in helping managers and clubs make the right decision to win leagues and tournaments. In this paper a logistic regression model is built to predict matches results of Barclays' Premier League season 2015/2016 for home win or away win and to determine what are the significant variable to win matches. Our work is different from others as we use only significant variables gathered from researches in the same field rather than making our own guess on what are the significant variables. We also used data gathered from video game FIFA, as Shin and Gasparyan [8] showed us that including data from the video game could improve prediction quality. The model was built using variations of training data from 2010/2011 season until 2015/2016. Logistic regression is a classification method which can be used to predict sports results and it can gives additional knowledge through regression coefficients. The variables used are “Home Offense”, “Home Defense”, “Away Offense”, and “Away Defense”. We conducted experiments by altering seasons of training data used. Prediction accuracy of built model is 69.5%. We found our work improved significantly compared to the one Snyder [9] did. We concluded that the significant variables are “Home Defense”, and “Away Defense”.","PeriodicalId":367414,"journal":{"name":"2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)","volume":"114 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131075691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 60

Developing corpus of Japanese-English Singular Sentence Textual Entailment 日英单数句语篇蕴涵语料库的开发

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803130

Daiki Hayakawa, Masatoshi Tsuchiya, H. Isahara

引用次数: 1

Extraction of phrases useful for machine translation 提取对机器翻译有用的短语

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803129

Kenta Saito, E. Yamamoto, Miki Ueno, Kyoko Kanzaki, H. Isahara

引用次数: 0

Robust Voice Activity Detector by combining sequentially trained Deep Neural Networks 结合顺序训练深度神经网络的鲁棒语音活动检测器

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803133

S. M. Raufun Nahar, A. Kai

引用次数: 5

Story creation system: Bringing up child's creativity with adult's interactive support by multimedia 故事创作系统:通过多媒体，在成人的互动支持下，培养孩子的创造力

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803139

Sanae Kuraya, S. Kamisato, Y. Ishida

引用次数: 0

Relation extraction using dependency tree kernel for Bahasa Indonesia 使用依赖树核提取印尼语的关系

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803105

Ditari Salsabila Esperanti, A. Purwarianti

{"title":"Relation extraction using dependency tree kernel for Bahasa Indonesia","authors":"Ditari Salsabila Esperanti, A. Purwarianti","doi":"10.1109/ICAICTA.2016.7803105","DOIUrl":"https://doi.org/10.1109/ICAICTA.2016.7803105","url":null,"abstract":"Most studies on relation extraction for Bahasa Indonesia were usually done by using string matching method. This approach lacked the syntactical information of the original text data. This paper offers an alternative approach of tree kernel method having advantage of preserving the sentence structure. Each sentence from the text is represented as a dependency parse tree. The tree kernel will calculate the similarity between the trees. Intuitively, the use of dependency structure would yield more accurate result since the related entities would closely connected to each other. Here, we compared our work with bag of word method. In the bag of word method, each pair of possibly related entities within the sentence, the shortest sub sentence containing both entities will be transformed into a feature vector. The similarity between two feature vectors will be calculated using a dot product. The experiments showed that the tree kernel method outperformed the bag of words method. On average, the tree kernel method yielded 77.3% on accuracy while the best bag of words method only had 71.8%. As a trade off, this method runs slower about ~50x longer than the bag of words method. At the final method, we tried the combined kernel and held the best result with 78.7% accuracy.","PeriodicalId":367414,"journal":{"name":"2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134262809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Development of an information system for efficient emergency transportation 发展有效的紧急运输信息系统

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA) Pub Date : 2016-08-01 DOI: 10.1109/ICAICTA.2016.7803085

M. Miyata, S. Tokunaga, Ren Ohmura

引用次数: 0