Mining intelligence and knowledge exploration : third International Conference, MIKE 2015, Hyderabad, India, December 9-11, 2015. Proceeedings. MIKE (Conference) (3rd : 2015 : Hyderabad, India)最新文献

筛选
英文 中文
Mining Intelligence and Knowledge Exploration: 7th International Conference, MIKE 2019, Goa, India, December 19–22, 2019, Proceedings 采矿智能与知识探索:第七届国际会议,MIKE 2019,印度果阿,2019年12月19-22日,会议录
Veena Thenkanidiyoor, R. Prasath, Odelu Vanga, R. Goebel, Yuzuru Tanaka
{"title":"Mining Intelligence and Knowledge Exploration: 7th International Conference, MIKE 2019, Goa, India, December 19–22, 2019, Proceedings","authors":"Veena Thenkanidiyoor, R. Prasath, Odelu Vanga, R. Goebel, Yuzuru Tanaka","doi":"10.1007/978-3-030-66187-8","DOIUrl":"https://doi.org/10.1007/978-3-030-66187-8","url":null,"abstract":"","PeriodicalId":91929,"journal":{"name":"Mining intelligence and knowledge exploration : third International Conference, MIKE 2015, Hyderabad, India, December 9-11, 2015. Proceeedings. MIKE (Conference) (3rd : 2015 : Hyderabad, India)","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75729754","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
Predicting Treatment Relations with Semantic Patterns over Biomedical Knowledge Graphs. 利用生物医学知识图的语义模式预测治疗关系。
Gokhan Bakal, Ramakanth Kavuluru
{"title":"Predicting Treatment Relations with Semantic Patterns over Biomedical Knowledge Graphs.","authors":"Gokhan Bakal,&nbsp;Ramakanth Kavuluru","doi":"10.1007/978-3-319-26832-3_55","DOIUrl":"https://doi.org/10.1007/978-3-319-26832-3_55","url":null,"abstract":"<p><p>Identifying new potential treatment options (say, medications and procedures) for known medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, <i>in vitro</i> approaches are first attempted to identify promising candidates. Even before this step, due to recent advances, <i>in silico</i> or computational approaches are also being employed to identify viable treatment options. Generally, natural language processing (NLP) and machine learning are used to predict specific relations between any given pair of entities using the distant supervision approach. In this paper, we report preliminary results on predicting treatment relations between biomedical entities purely based on semantic patterns over biomedical knowledge graphs. As such, we refrain from explicitly using NLP, although the knowledge graphs themselves may be built from NLP extractions. Our intuition is fairly straightforward - entities that participate in a treatment relation may be connected using similar path patterns in biomedical knowledge graphs extracted from scientific literature. Using a dataset of treatment relation instances derived from the well known Unified Medical Language System (UMLS), we verify our intuition by employing graph path patterns from a well known knowledge graph as features in machine learned models. We achieve a high recall (92 %) but precision, however, decreases from 95% to an acceptable 71% as we go from uniform class distribution to a ten fold increase in negative instances. We also demonstrate models trained with patterns of length ≤ 3 result in statistically significant gains in F-score over those trained with patterns of length ≤ 2. Our results show the potential of exploiting knowledge graphs for relation extraction and we believe this is the first effort to employ graph patterns as features for identifying biomedical relations.</p>","PeriodicalId":91929,"journal":{"name":"Mining intelligence and knowledge exploration : third International Conference, MIKE 2015, Hyderabad, India, December 9-11, 2015. Proceeedings. MIKE (Conference) (3rd : 2015 : Hyderabad, India)","volume":"9468 ","pages":"586-596"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-319-26832-3_55","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35204923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信