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WUST at the NTCIR-17 FinArg-1 Task
Get PDFhis article introduces how we deal with the FinArg-1 task of NTCIR17. In the FinArg-1 task, we have completed three subtasks which are argument classification, argument relation identification, and identifying relations in the social media dataset. In the experiments, we use the Bert model for the FinArg-1 three subtasks module.conference pape
KIS’s Stance Classification Model at the NTCIR-17 QA Lab-PoliInfo-4
Get PDFWe participated in the Stance Classification 2 (SC2) subtask of NTCIR-17 QA Lab-PoliInfo-4 as Team KIS. In this paper, we describe ourstance (agreement or disagreement) classification model for utter-ances of Japanese politicians with domain-adaptive training in thepolitical domain. We additionally trained the Japanese pretrainedLUKE model with a Masked Language Model (MLM) on the Dietminutes dataset. We also preprocessed the model using the head-tail method to truncate utterances longer than the maximum inputlength. We found that these methods were effective, achieved thehighest score of 97.41% in accuracy in the formal run of the sub-task.conference pape
IMNTPU at the NTCIR-17 FinArg-1: Financial Argument-Based Sentiment Analysis and Argumentative Relations Identification in Social Media
Get PDFIn recent years, there has been a surge of interest in argument-based sentiment analysis and the identification of argumentative relationships in social media. These tasks encompass sentiment analysis of premises and claims, as well as the classification of argumentative relationships. Within these tasks, we have developed a fine-tuning method for transformer models. To evaluate and showcase this concept, we established a comprehensive framework to test and display the performance of BERT, RoBERTa, FinBERT, ALBERT, and GPT 3.5-turbo models on financial data and social media texts. Ultimately, the experimental results of these sub-tasks validate the effectiveness of our strategies. The primary contribution of our research is our proposal of two key elements: fine-tuning predominantly with BERT models and employing GPT for generative classification, aiming to enhance the identification of argumentative classifications. Through fine-tuning techniques, the state-of-the-art models can achieve better performance than the baseline.conference pape
BITIR at the NTCIR-17 Session Search Task
Get PDFThe BITIR team participated in the IR subtask of the NTCIR-17 Session Search(SS) Task.This paper reports our approach to solving the problem and discusses the official results.More specifically, for FOSS and POSS tasks, we submit two times by using the classical retrieval model BM25 and graph-based context-aware document ranking model HEXA. Results show that our runs perform well on the test dataset with relevance label, but poorly on the official test dataset provided This may be due to the problem of noise and a small candidate set. For SSEE task, We use two traditional metrics: sDCG and sRBP. The result indicates that sRBP has a higher consistency with golden user satisfaction based on our settings.conference pape
Overview of the NTCIR-17 FinArg-1 Task: Fine-Grained Argument Understanding in Financial Analysis
Get PDFThis paper provides an overview of FinArg-1 shared tasks in NTCIR-17. We propose six subtasks with three different resources, including company manager presentations, professional analyst reports, and social media posts. 19 research teams registered for FinArg-1, and 11 teams submitted their system output for official evaluation.conference pape
THUIR_SS at the NTCIR-17 Session Search (SS) Task
Get PDFSession Search holds significant importance in the field of information retrieval and user experience. In this paper, we detail the approach of the THUIR_SS team in the NTCIR17 Session Search (SS-2) task. Specifically, we submit five runs for FOSS and POSS tasks respectively. We try different approaches to feature fusion, including learning to rank and linearly combination. The final report of the SS-2 Taskdemonstrate the effectiveness of our method, significantly outperforming other competitors.conference pape
ダイ 37 カイ コレカラ ノ ガクジュツ ジョウホウ システム コウチク ケントウ イインカイ ハイフシリョウ
Get PDF会議名：第37回 これからの学術情報システム構築検討委員会
開催場所：国立情報学研究所
日時：2023年10月4日（水）15:00～17:00conference outpu
海外研修経験から見えた大学図書館
Get PDF研修名：2023年度大学図書館職員短期研修
開催期間：2023年10月17日（火）～10月20日（金）
主催：東京大学附属図書館、京都大学附属図書館、国立情報学研究所othe
第26回大学図書館と国立情報学研究所との連携・協力推進会議配布資料
Get PDF会議名：第26回大学図書館と国立情報学研究所との連携・協力推進会議
開催場所：オンライン
日時：2023年7月6日（木）13:00～15:00conference objec
SPARC Japan セミナー2022 「電子ジャーナルの転換契約とAPC問題で変わるオープンアクセスの現状と課題」 #転換契約 は#電⼦ジャーナル問題 を解決できるか︖ 発表資料
Get PDFSPARC Japan セミナー2022「電子ジャーナルの転換契約とAPC問題で変わるオープンアクセスの現状と課題」
開催場所：オンライン開催
日時：2023年2月17日（金）13:00-17:00conference objec