2015 26th International Workshop on Database and Expert Systems Applications (DEXA)最新文献_第3页

Distance Based Queries in Open Street Map 开放街道地图中基于距离的查询

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.60

J. Almendros-Jiménez, A. Becerra-Terón

引用次数: 1

Smart Indoor Positioning System for Situation Awareness in Emergency Situations 面向紧急情况的智能室内定位系统

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.44

Lazar Berbakov, Bogdan Pavković, S. Vranes

引用次数: 8

A Semantic Knowledge Management System for Government Repositories 面向政府知识库的语义知识管理系统

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.48

E. Tello-Leal, Ana B. Ríos-Alvarado, Alan Díaz-Manríquez

{"title":"A Semantic Knowledge Management System for Government Repositories","authors":"E. Tello-Leal, Ana B. Ríos-Alvarado, Alan Díaz-Manríquez","doi":"10.1109/DEXA.2015.48","DOIUrl":"https://doi.org/10.1109/DEXA.2015.48","url":null,"abstract":"Nowadays, in a knowledge-driven economy, the organizations, public or private, require to make an appropriate managing knowledge assets to sustain competitive edge in global markets or in governmental services. Advances in Information and Communications Technologies have supported innovations in Knowledge Management (KM). Since the KM has been recognized as one of the critical factors for obtaining organizational competitiveness. KM is among the promising areas for the application of Semantic Web. In this paper we propose an approach to the development of a technological platform for KM that integrates semantic Web technologies. This platform supports all processes required in knowledge management. Therefore, the platform enables the automatic identification of patterns and generation of the taxonomies from unstructured texts (documents). The platform consists of tools that allow storing documents (from a knowledge contributor interface), processing of source documents, i.e. identifying sentences, stop-words, identifying n-grams, and generating bags of words, denoting lexical patterns, taxonomic-relation extraction, and inference algorithms to retrieve knowledge from a set of repositories. These algorithms use the previous phases to retrieve knowledge more accurately derived from the semi-structured or structured information previously generated.","PeriodicalId":239815,"journal":{"name":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","volume":"186 5 Suppl Nature 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116384650","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: 5

Web Services Clustering Using a Bio-inspired Algorithm 使用生物启发算法的Web服务集群

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.52

Roman Mora, Saul Santillan-Perez, Maricela Claudia Bravo

引用次数: 1

Multi-agent Electricity Markets: A Case Study on Contracts for Difference 多主体电力市场:差价合约案例研究

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.35

Francisco Sousa, F. Lopes, J. Santana

引用次数: 9

The Role of Machine Learning in Finding Chimeric RNAs 机器学习在寻找嵌合rna中的作用

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.25

S. Beaumeunier, J. Audoux, A. Boureux, T. Commes, Nicolas Philippe, Ronnie Alves

{"title":"The Role of Machine Learning in Finding Chimeric RNAs","authors":"S. Beaumeunier, J. Audoux, A. Boureux, T. Commes, Nicolas Philippe, Ronnie Alves","doi":"10.1109/DEXA.2015.25","DOIUrl":"https://doi.org/10.1109/DEXA.2015.25","url":null,"abstract":"High-throughput sequencing technology and bioinformatics have identified chimeric RNAs (chRNAs), raising the possibility of chRNAs expressing particularly in diseases can be used as potential biomarkers in both diagnosis and prognosis. The task of discriminating true chRNA from the false ones poses an interesting Machine Learning (ML) challenge. First of all, the sequencing data may contain false reads due to technical artefacts and during the analysis process, bioinformatics tools may generate false positives due to methodological biases. Thus predicting the real signal from the noise can be a hard task. Furthermore, even if we succeed to have a proper set of observations (enough sequencing data) about true chRNAs, chances are that the devised model can not be able to generalize beyond it. Like any other machine learning problem, the first big issue is finding the good data, observations, to build the prediction model. Unfortunately, as far as we were concerned, there is no common benchmark data available for chRNAs. And, the definition of a classification baseline is lacking in the related literature. In this work we are moving towards a benchmark data and a fair comparison analysis unraveling the role of ML techniques in finding chRNAs. We have developed a benchmark pipeline incorporating a mutated genome process and simulated RNA-seq data by Flux Simulator. These sequencing reads were aligned and annotated by CRAC. CRAC offers a new way to analyze the RNA-seq data by integrating genomic location and local coverage, allowing biological predictions in one step. The resulting data were used as a benchmark for our comparison analysis. We have observed that the no free lunch theorem do not hold for ensemble classifiers. Ensemble learning strategies demonstrated to be more robust to this classification problem, providing an average AUC performance of 95% (ACC=94%, Kappa=0.87%).","PeriodicalId":239815,"journal":{"name":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125111148","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

A Meta-model Based Approach for Data Warehouses Design and Implementation 基于元模型的数据仓库设计与实现方法

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.56

Leopoldo Zepeda-Sánchez, Luis C. Santillán, Elizabeth Ceceña, Emir Manjarrez, L. Vega, C. García

引用次数: 0

Portfolio Optimization for Electricity Market Participation with Particle Swarm 基于粒子群的电力市场投资组合优化

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.31

Ricardo Faia, T. Pinto, Z. Vale, E. Pires

{"title":"Portfolio Optimization for Electricity Market Participation with Particle Swarm","authors":"Ricardo Faia, T. Pinto, Z. Vale, E. Pires","doi":"10.1109/DEXA.2015.31","DOIUrl":"https://doi.org/10.1109/DEXA.2015.31","url":null,"abstract":"The liberalization of energy markets has imposed several modifications in the electricity market environment. The paradigm of monopoly market ceased to exist, and new models have been put into practice. The new models have increased the incentive on competitiveness, making market players struggle to achieve the best outcomes out of market participation. Producers aim at reaching the maximum profit on the sale of energy, while consumers try to minimize their spending on electrical energy. The proposed methodology considers the optimization of players' participation in multiple market opportunities. Reference prices that are expected in each market type at each moment are achieved through the application of neural networks. Using the forecasted prices, the proposed portfolio optimization method allocates the sale and purchase of electrical energy to different markets throughout the time, with the aim at achieving the most advantageous participation profile. A particle swarm approach is used to reduce the execution time while guaranteeing the minimum degradation of the results. Results of the swarm methodology are compared to those of a deterministic approach, using real data from the Iberian electricity market - MIBEL.","PeriodicalId":239815,"journal":{"name":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128916944","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: 5

Extraction of Definitional Contexts through Machine Learning 通过机器学习提取定义上下文

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.57

Víctor Mijangos, Gerardo E Sierra

引用次数: 0

Data, Information & Knowledge Sources in the Agricultural Domain 农业领域的数据、信息和知识来源

2015 26th International Workshop on Database and Expert Systems Applications (DEXA) Pub Date : 2015-09-01 DOI: 10.1109/DEXA.2015.40

Markus Jäger, Stefan Nadschläger, T. Phan, J. Küng

引用次数: 2