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TitleMining opinion holders and opinion patterns in US financial statements
CreatorChen, Chien-Liang;Liu, Chao-Lin;Chang, Yuan-Chen;Tsai, Hsiang-Ping
陳建良;劉昭麟;張元晨;蔡湘萍
Contributor資科系;語言所
Key WordsConditional random field; Information extraction; Opinion mining; Semantic labeling; Sentiment analysis; Text mining; Artificial intelligence; Finance; Image segmentation; Quality control; Random processes; Semantics; Data mining
Date2011-11
Date Issued8-Apr-2015 17:34:09 (UTC+8)
SummarySubjective statements provide qualitative evaluation of the financial status of the reporting corporations, in addition to the quantitative information released in US 10-K filings. Both qualitative and quantitative appraisals are crucial for quality financial decisions. To extract such opinioned statements from the reports, we built tagging models based on the conditional random field (CRF) techniques, considering a variety of combinations of linguistic factors including morphology, orthography, predicate-argument structure, syntax and simple semantics. The CRF models showed reasonable effectiveness to find opinion holders in experiments when we adopted the popular MPQA corpus for training and testing. We also identified opinion patterns in the form of multi-word expressions (MWEs), which is a major contribution of our work. In a recent article published in a prestigious journal in Finance, single words, rather than MWEs, were reported to indicate positive and negative judgments in financial statements. © 2011 IEEE.
RelationProceedings - 2011 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2011, 論文編號 6120721, 62-68 最佳論文佳作獎, 中華民國人工智慧學會
10.1109/TAAI.2011.19
Typeconference
dc.contributor 資科系;語言所
dc.creator (作者) Chen, Chien-Liang;Liu, Chao-Lin;Chang, Yuan-Chen;Tsai, Hsiang-Ping
dc.creator (作者) 陳建良;劉昭麟;張元晨;蔡湘萍zh_TW
dc.date (日期) 2011-11
dc.date.accessioned 8-Apr-2015 17:34:09 (UTC+8)-
dc.date.available 8-Apr-2015 17:34:09 (UTC+8)-
dc.date.issued (上傳時間) 8-Apr-2015 17:34:09 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/74409-
dc.description.abstract (摘要) Subjective statements provide qualitative evaluation of the financial status of the reporting corporations, in addition to the quantitative information released in US 10-K filings. Both qualitative and quantitative appraisals are crucial for quality financial decisions. To extract such opinioned statements from the reports, we built tagging models based on the conditional random field (CRF) techniques, considering a variety of combinations of linguistic factors including morphology, orthography, predicate-argument structure, syntax and simple semantics. The CRF models showed reasonable effectiveness to find opinion holders in experiments when we adopted the popular MPQA corpus for training and testing. We also identified opinion patterns in the form of multi-word expressions (MWEs), which is a major contribution of our work. In a recent article published in a prestigious journal in Finance, single words, rather than MWEs, were reported to indicate positive and negative judgments in financial statements. © 2011 IEEE.
dc.format.extent 258657 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Proceedings - 2011 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2011, 論文編號 6120721, 62-68 最佳論文佳作獎, 中華民國人工智慧學會
dc.relation (關聯) 10.1109/TAAI.2011.19
dc.subject (關鍵詞) Conditional random field; Information extraction; Opinion mining; Semantic labeling; Sentiment analysis; Text mining; Artificial intelligence; Finance; Image segmentation; Quality control; Random processes; Semantics; Data mining
dc.title (題名) Mining opinion holders and opinion patterns in US financial statements
dc.type (資料類型) conferenceen