2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)最新文献_第6页

A trust-enriched approach for item-based collaborative filtering recommendations 基于项目的协同过滤推荐的一种增强信任的方法

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2016-09-01 DOI: 10.1109/ICCP.2016.7737124

Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, M. O'Droma

引用次数: 17

Harmonization of conflicting medical opinions using argumentation protocols and textual entailment - a case study on Parkinson disease 使用论证协议和文本蕴涵协调相互冲突的医学意见-帕金森氏病的案例研究

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2016-07-27 DOI: 10.1109/ICCP.2016.7737140

Adrian Groza, Madalina Mandy Nagy

{"title":"Harmonization of conflicting medical opinions using argumentation protocols and textual entailment - a case study on Parkinson disease","authors":"Adrian Groza, Madalina Mandy Nagy","doi":"10.1109/ICCP.2016.7737140","DOIUrl":"https://doi.org/10.1109/ICCP.2016.7737140","url":null,"abstract":"Parkinson's disease is the second most common neurodegenerative disease, affecting more than 1.2 million people in Europe. Medications are available for the management of its symptoms, but the exact cause of the disease is unknown and there is currently no cure on the market. To better understand the relations between new findings and current medical knowledge, we need tools able to analyze published medical papers based on natural language processing and tools capable of identifying various relationships of new findings with the current medical knowledge. Our work aims to fill the above technological gap. To identify conflicting information in medical documents, we enact textual entailment technology. To encapsulate existing medical knowledge, we rely on ontologies. To connect the formal axioms in ontologies with natural text in medical articles, we exploit ontology verbalization techniques. To assess the level of disagreement between human agents with respect to a medical issue, we rely on fuzzy aggregation. To harmonize this disagreement, we design mediation protocols within a multi-agent framework.","PeriodicalId":343658,"journal":{"name":"2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121384401","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: 0

Mining arguments from cancer documents using Natural Language Processing and ontologies 使用自然语言处理和本体从癌症文档中挖掘论点

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2016-07-27 DOI: 10.1109/ICCP.2016.7737126

Adrian Groza, Oana Popa

{"title":"Mining arguments from cancer documents using Natural Language Processing and ontologies","authors":"Adrian Groza, Oana Popa","doi":"10.1109/ICCP.2016.7737126","DOIUrl":"https://doi.org/10.1109/ICCP.2016.7737126","url":null,"abstract":"In the medical domain, the continuous stream of scientific research contains contradictory results supported by arguments and counter-arguments. As medical expertise occurs at different levels, part of the human agents have difficulties to face the huge amount of studies, but also to understand the reasons and pieces of evidences claimed by the proponents and the opponents of the debated topic. To better understand the supporting arguments for new findings related to current state of the art in the medical domain we need tools able to identify arguments in scientific papers. Our work here aims to fill the above technological gap. We rely on the well-known interleaving of domain knowledge with natural language processing. To formalise the existing medical knowledge, we rely on ontologies. To structure the argumentation model we use also the expressivity and reasoning capabilities of Description Logics. To perform argumentation mining we formalise various linguistic patterns in a rule-based language. We tested our solution against a corpus of scientific papers related to breast cancer. The run experiments show a F-measure between 0.71 and 0.86 for identifying conclusions of an argument and between 0.65 and 0.86 for identifying premises of an argument.","PeriodicalId":343658,"journal":{"name":"2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134620335","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

Assisting drivers during overtaking using Car-2-Car communication and multi-agent systems 利用Car-2-Car通信和多智能体系统协助司机超车

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2016-07-27 DOI: 10.1109/ICCP.2016.7737162

Adrian Groza, Calin Cara, S. Zaporojan, Igor Calmicov

引用次数: 3