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Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets最新文献

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Extracting Knowledge Graphs from Financial Filings: Extended Abstract 从财务文件中提取知识图谱:扩展摘要
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077246
J. Pujara
{"title":"Extracting Knowledge Graphs from Financial Filings: Extended Abstract","authors":"J. Pujara","doi":"10.1145/3077240.3077246","DOIUrl":"https://doi.org/10.1145/3077240.3077246","url":null,"abstract":"Textual corpora, such as financial documents, contain a wealth of knowledge. Recently, knowledge graphs have become a popular approach to capturing structured knowledge of entities and their interrelationships. In this paper, we evaluate open information extraction (IE) and knowledge graph construction techniques for assessing the relevance of textual segments in the Financial Entity Identification and Information Integration Challenge. Our approach is to extract several textual signals, including topics and open IE triples, and combine these in a probabilistic framework to predict the relevance of each potential relationship.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116401966","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
Financial Entity Identification and Information Integration (FEIII) 2017 Challenge: The Report of the Organizing Committee 金融实体识别与信息集成(FEIII) 2017挑战赛:组委会报告
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077248
L. Raschid, D. Burdick, M. Flood, John Grant, J. Langsam, I. Soboroff
{"title":"Financial Entity Identification and Information Integration (FEIII) 2017 Challenge: The Report of the Organizing Committee","authors":"L. Raschid, D. Burdick, M. Flood, John Grant, J. Langsam, I. Soboroff","doi":"10.1145/3077240.3077248","DOIUrl":"https://doi.org/10.1145/3077240.3077248","url":null,"abstract":"This report presents the goals and outcomes of the 2017 Financial Entity Identification and Information Integration (FEIII) Challenge. We describe the dataset and challenge task and the protocol to create labeled data. The report summarizes the process, outcomes and plans for the 2018 Challenge.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117116473","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
Hybrid Feature Factored System for Scoring Extracted Passage Relevance in Regulatory Filings 混合特征因子系统评分提取通道相关性在监管文件
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077251
Denys Proux, Claude Roux, Ágnes Sándor, Julien Perez
{"title":"Hybrid Feature Factored System for Scoring Extracted Passage Relevance in Regulatory Filings","authors":"Denys Proux, Claude Roux, Ágnes Sándor, Julien Perez","doi":"10.1145/3077240.3077251","DOIUrl":"https://doi.org/10.1145/3077240.3077251","url":null,"abstract":"We report in this paper our contribution to the FEIII 2017 challenge addressing relevance ranking of passages extracted from 10-K and 10-Q regulatory filings. We leveraged our previous work on document structure and content analysis for regulatory filings to train hybrid text analytics and decision making models. We designed and trained several layers of classifiers fed with linguistic and semantic features to improve relevance prediction. We discuss in this paper our experiments and results on the competition data set.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132764825","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
FactSet: The Advantage of Scored Data FactSet:得分数据的优势
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077256
R. Hicks
{"title":"FactSet: The Advantage of Scored Data","authors":"R. Hicks","doi":"10.1145/3077240.3077256","DOIUrl":"https://doi.org/10.1145/3077240.3077256","url":null,"abstract":"","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129670224","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
Comparing Features for Ranking Relationships Between Financial Entities based on Text 基于文本的金融实体关系排序特征比较
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077252
Tim Repke, M. Loster, Ralf Krestel
{"title":"Comparing Features for Ranking Relationships Between Financial Entities based on Text","authors":"Tim Repke, M. Loster, Ralf Krestel","doi":"10.1145/3077240.3077252","DOIUrl":"https://doi.org/10.1145/3077240.3077252","url":null,"abstract":"","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129856935","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
Towards Re-defining Relation Understanding in Financial Domain 重新定义金融领域的关系理解
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077254
Chenguang Wang, D. Burdick, Laura Chiticariu, R. Krishnamurthy, Yunyao Li, Huaiyu Zhu
{"title":"Towards Re-defining Relation Understanding in Financial Domain","authors":"Chenguang Wang, D. Burdick, Laura Chiticariu, R. Krishnamurthy, Yunyao Li, Huaiyu Zhu","doi":"10.1145/3077240.3077254","DOIUrl":"https://doi.org/10.1145/3077240.3077254","url":null,"abstract":"We describe our experiences in participating in the scored task for the 2017 FEIII Data Challenge. Our approach is to model the problem as a binary classification problem and train an ensemble model leveraging domain features that capture financial terminology. We share challenge results for our submission, which performed well achieving the highest score in four out of six evaluation criteria. We describe semantic complexities encountered with regards to the task definition and ambiguities in the labeled dataset. We present an alternative task formulation Relationship Validation that addresses some of these semantic complexities and demonstrate how our approach naturally extends to this simplified task definition.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121912616","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
Entity relationship ranking using differential keyword-role affinity 使用差分关键字-角色亲和度对实体关系进行排序
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077255
Rohit Naini, Pawan Yadav
{"title":"Entity relationship ranking using differential keyword-role affinity","authors":"Rohit Naini, Pawan Yadav","doi":"10.1145/3077240.3077255","DOIUrl":"https://doi.org/10.1145/3077240.3077255","url":null,"abstract":"Identifying relationship between named entities from a corpus of text is a well studied NLP problem. In this paper, we consider a tractable version of this wherein sample text snippets and corresponding roles are extracted and need to be ranked on relevance of text to the role. Our scoring approach uses a cumulative estimated relevance of all keywords observed in the text snippet. Relevance metrics are computed based on differential affinity of keywords to the roles observed in the training data.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122153578","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: 3
Exploring Financial Relationships Using Probabilistic Topic Models (Demonstration Paper) 利用概率主题模型探索金融关系(演示论文)
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077247
L. Raschid, Zheng Xu, Elena Zotkina
{"title":"Exploring Financial Relationships Using Probabilistic Topic Models (Demonstration Paper)","authors":"L. Raschid, Zheng Xu, Elena Zotkina","doi":"10.1145/3077240.3077247","DOIUrl":"https://doi.org/10.1145/3077240.3077247","url":null,"abstract":"Understanding relationships among financial entities can provide insight into the behavior of complex financial eco-systems. In this demonstration paper, we consider datasets of financial documents that describe the activity or role played by a financial institution (FI), typically with respect to a financial product or another financial entity. We develop community models based on financial institutions (FI) and their behavior or activity described by their roles (Role). Our models are based on an intuitive assumption that FIs will form communities, and FIs within a community are more likely to collaborate with other FIs in that community, and to play the same role, in other communities. Inspired by the Latent Dirichlet Allocation (LDA) and topic models, we develop several probabilistic financial community models and we use those models to identify interesting financial communities in two datasets.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130348652","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
Thomson Reuters' Submission to the FEIII 2017 Challenge Non-scored Tasks 汤森路透提交的FEIII 2017挑战非计分任务
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077244
E. Roman, B. Ulicny, Yi Du, Srijith Poduval, A. Ko
{"title":"Thomson Reuters' Submission to the FEIII 2017 Challenge Non-scored Tasks","authors":"E. Roman, B. Ulicny, Yi Du, Srijith Poduval, A. Ko","doi":"10.1145/3077240.3077244","DOIUrl":"https://doi.org/10.1145/3077240.3077244","url":null,"abstract":"In this paper we describe a machine learning approach to predict roles of extracted SEC triples for the non-scored task of the 2017 FEIII Challenge. In addition, we describe a graph and data analysis derived from SEC triples.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134139245","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
Web Text-based Network Industry Classifications: Preliminary Results 基于Web文本的网络行业分类:初步结果
Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets Pub Date : 2017-05-14 DOI: 10.1145/3077240.3077245
Eric Heiden, Gerard Hoberg, Craig A. Knoblock, Palak Modi, G. Phillips, Gaurangi Raul, Pedro A. Szekely
{"title":"Web Text-based Network Industry Classifications: Preliminary Results","authors":"Eric Heiden, Gerard Hoberg, Craig A. Knoblock, Palak Modi, G. Phillips, Gaurangi Raul, Pedro A. Szekely","doi":"10.1145/3077240.3077245","DOIUrl":"https://doi.org/10.1145/3077240.3077245","url":null,"abstract":"Studies of market structure and product market competition are important in many disciplines, such as economics, finance, accounting and management. Reliable data for such studies is easily available for public firms (e.g., 10-K filings), but no reliable data exists for private firms. In this work we propose to mine the Internet Archive Wayback Machine, a digital archive of the World Wide Web, to build a database of 300,000 companies to support analyses of market structure, product market competition, and innovation. The goal of the WTNIC project is to download pages from the archive to build a profile for each company, and to use machine learning techniques to define similarity between companies based on similarity of their product and service offerings. This paper describes the challenges that must be overcome, our approach to overcome these challenges, and some preliminary results.","PeriodicalId":326424,"journal":{"name":"Proceedings of the 3rd International Workshop on Data Science for Macro--Modeling with Financial and Economic Datasets","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132195755","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
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