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fuys Team at the NTCIR-17 UFO Task
Get PDFThis paper reports the results of the fuys team's NTCIR-17 UFO Text-to-Table Relationship Extraction (TTRE). Since we thought that Value cells depend on Name cells, we came up with a method that uses the result of extracting Name cells to connect them together. The text of a HTML tag and texts of cells were used to find Name. These two were encoded and combined to perform a binary classification. We tried several combinations of mark tag text and cell text. The best results were obtained using mark tags and tables in the same section of the same company. We tried two different rules for binding Value cells. The rule of finding a cell by the row and column combination of the cell that became the Name yielded good results.conference pape
Forst: A Challenge to the NTCIR-17 QA Lab-PoliInfo-4 Task
Get PDFIn this paper, we describe our work on Answer Verification. We submitted one result to Answer Verification. The method used for the submitted data is to input the "AnswerSummary," "AnswerOriginal," and "QuestionSummary" items together and have ChatGPT classify them. As a result, an Accuracy of 0.5800 for the Answer Verification was obtained.conference pape
MONETECH at the NTCIR-17 FinArg-1 Task: Layer Freezing, Data Augmentation, and Data Filtering for Argument Unit Identification
Get PDFThis paper reports MONETECH's participation in FinArg-1's Argument Unit Identification in Earnings Conference Call subtask. Our experiments are based on the BERT and FinBERT models with additional experimentation on Large Language Model-based data augmentation, data filtering, and the model's layer freezing. Our best-performing submission, which is based on data filtering and the model's layer freezing, scores 75.54\% in micro F1 evaluation. Results from additional runs also show that the model's layer freezing and data filtering could further improve model performance beyond our best submission.conference pape
Overview of the NTCIR-17 Unbiased Learning to Rank Evaluation 2 (ULTRE-2) Task
Get PDFIn this paper, we present an overview of the Unbiased Learning to Rank Evaluation 2 (ULTRE-2) task, a pilot task at the NTCIR-17. The ULTRE-2 task aims to evaluate the effectiveness of unbiased learning to rank (ULTR) models with a large-scale user behavior log collected from Baidu.com, a commercial Web search engine. In this paper, we describe the task specification, dataset construction, implemented baselines, and official evaluation results of the submitted runs.conference pape
NTCIR-17 MedNLP-SC Radiology Report Subtask Overview: Dataset and Solutions for Automated Lung Cancer Staging
Get PDFThis paper describes the Radiology Report TNM staging (RR-TNM) subtask as a part of NTCIR-17 Medical Natural Language Processing for Social Media and Clinical Texts (MedNLP-SC) shared task in 2023. This subtask focused on automated lung cancer staging based on radiology reports. We created a dataset of 243 Japanese radiology reports containing no personal health information. A total of three teams with 16 members participated and submitted seven solutions. The best accuracy scores for the T, N, and M categories reached 67%, 80%, and 93%, respectively. Through the RR- TNM subtask, we have provided a valuable open Japanese clinical corpus and useful insights to apply natural language processing for secondary usage of staging information.conference pape
MEMORIA: A Memory Enhancement and MOment RetrIeval Application at the NTCIR-17 Lifelog-5 Task
Get PDFIn recent years, the practice of continuously recording and collecting information about several aspects of individuals’ lives has gained increased popularity. This practice, known as lifelogging, serves multiple purposes, including personal health monitoring and enhancement as well as recording day-to-day activities in hopes of preserving some memories. An essential aspect of this practice lies in the gathering and analysis of image data, offering valuable insights into an individual’s lifestyle, dietary patterns, and physical activities. The NTCIR Lifelog Challenge presents a unique opportunity to delve into the latest advancements in lifelogging research, particularly in the field of image retrieval and analysis. Researchers are encouraged to present their methodologies and participate in lifelog retrieval challenges. Consequently, these challenges allow research teams to assess the efficiency and accuracy of their developed systems using a multimodal dataset derived from an active lifelogger’s 18 months of continuous lifelogging data. This paper presents the current version of MEMORIA, a computational tool that provides an intuitive user interface with several options that allow the user to upload images, explore the segmented events, and perform image retrieval, namely images for the NTCIR Lifelog event. This version of MEMORIA incorporates natural language search capabilities for information retrieval, offering options to filter results based on keywords and time periods. The system integrates image analysis algorithms to process visual lifelogs. These algorithms range from pre-processing algorithms to feature extraction methods, to enrich the annotation of the lifelogs. The paper also includes experimental results of the image annotation methods used in MEMORIA, as well as some examples of user interaction.conference pape
Fairness-based Evaluation of Conversational Search: A Pilot Study
Get PDFNTCIR-17 introduced the FairWeb-1 task,which evaluated web page rankingsin terms of both relevance and group fairness.The present study shows how their evaluation frameworkcan be extended for the evaluation ofmulti-turn, textual conversational search systems.By using the full test topic set of FairWeb-1to harvest actual user-system conversations from the New Bing and Google Bard,we demonstrate how a series of system turns can be evaluatedusing our evaluation framework,which we callGFRC (Group Fairness and Relevance of Conversations).In addition, based onobservations from our pilot experiment,we briefly discuss a few open questions in human-in-the-loopevaluation of conversational search in general.conference pape
日本目録規則2018年版への対応について
Get PDF研修名：2023年度目録システム書誌作成研修
開催日：2023年9月14日（木）、9月15日（金）、11月17日（金）
主催：国立情報学研究所othe
SPARC Japan セミナー2023 「即時OAに備えて：論文・データを「つかってもらう」ためのライセンス再入門」 J-STAGE Dataの現状とライセンスについて ドキュメント
Get PDFSPARC Japan セミナー2023「即時OAに備えて：論文・データを「つかってもらう」ためのライセンス再入門」
開催場所：オンライン開催
日時：2023年11月28日（火）13:00～17:00conference objec