NTCIR

第15回 NTCIR (2019 - 2020)
情報アクセス技術研究のためのテストベッドとコミュニティ
カンファレンス: 2020年12月8日(火)～11日(金) 東京 学術総合センター

NTCIR-15 タスク参加のご案内:

参加申込の手引き

NTCIRの目的: http://research.nii.ac.jp/ntcir/ntcir-15/aims-ja.html

第15回NTCIR（NTCIR-15）タスク選考委員会は、以下の5つのコアタスクと2つのパイロットタスクを選定しました。
タスク紹介スライド（キックオフイベント）を下記のページからご覧いただけます：
タスク紹介スライド（キックオフイベント）: http://research.nii.ac.jp/ntcir/ntcir-15/kickoff-ja.html
タスクの詳細・最新情報について、下記のタスク概要および各タスクのウェブサイトをご覧ください。

DialEval-1     FinNum-2     QA Lab-PoliInfo-2     SHINRA2020-ML     WWW-3     Data Search     MART    

コアタスク

Dialogue Evaluation ("DialEval-1")

"顧客・ヘルプデスク対話を入力とし、対話全体の品質を推定する and/or 顧客・ヘルプデスクの各ターンを分類する"

Abstract:
DQ: Given a customer-helpdesk dialogue, return an estimated distribution of dialogue quality ratings for the entire dialogue.
ND: Given a customer-helpdesk dialogue, return an estimated distribution of labels over nugget types (similar to dialogue acts) for each turn.
Data: Chinese and English
For more information, please visit: http://sakailab.com/dialeval1/

Website: http://sakailab.com/dialeval1/
Contact:

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Numeral Attachment in Financial Tweets("FinNum-2")

"Numeral attachment in financial tweets"

Abstract:
In order to understanding the numeral information in depth, we proposed a task in NTCIR-14 to disambiguate the meaning of the numerals in financial social media data. However, only understanding the meanings of numerals is not enough for practical uses, because there may has more than one cashtag in a financial tweet. Understanding their semantic roles in the financial social media data is needed when mining fine-grained opinions toward a certain target.
Along this line, we design another novel task for fine-grained numeral understanding in financial social media data, called numeral attachment, which aims to detect the attached target (i.e., cashtag) of the numeral. That is, we attempt to understand that the numeral is attached to which cashtag in a tweet. For example, there are two cashtags and one numeral in (T1). The numeral "36.50" is related to $BEXP, instead of $KOG.
(T1) $KOG Took a small position- hopefully a better outcome than getting kneecapped by $BEXP selling itself dirt cheap at 36.50

Website: https://sites.google.com/nlg.csie.ntu.edu.tw/finnum2020
Contact:

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Question Answering Lab for Political Information ("QA Lab-PoliInfo-2")

"地方議会会議録の要約、発話者のスタンス分類、同一条例の推定"

Abstract:
We propose the QA Lab-PoliInfo-2 (Question Answering Lab for Political Information 2) task at NTCIR 15 is aimed to verify the credibility of political information including fake news, using complex real-world question answering (QA) technologies.

Website: http://poliinfo2.net/
Contact: qalab-admin

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SHINRA 2020 Multi-lingual("SHINRA2020-ML")

"30言語のWikipedia記事を拡張固有表現に分類する"

Abstract:
Based on manually categorized Japanese Wikipedia pages and the language links between Wikipedia pages in different languages, the task is to categorize the entire 30 language Wikipedia pages into Extended Named Entity. We expect the participants to use the Wikipedia pages with the link from Japanese Wikipedia as the training data, and run the system to categorize the remaining Wikipedia pages which don't have language links. After the task is over, we (including the participants) will combine the results by all the participants (i.e. by Ensemble learning), and publish the results to the public. It is a scheme called "Resource by Collaborative Contribution (RbCC)" and we are expecting many participants with a good will.

Website: http://shinra-project.info/shinra2020ml/?lang=en
Contact:

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We Want Web with CENTRE ("WWW-3")

"アドホックWeb検索。複製可能性・再現可能性の検証も可"

Abstract:
The Chinese subtask is an adhoc web search task where a large query log data can be utilised. The English subtask is an adhoc web search task where not only regular adhoc runs but also replicated/reproduced runs are evaluated. All runs are required to process both the WWW-2 topics and the new WWW-3 topics.

Website: http://sakailab.com/www3/
Contact:

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パイロットタスク

Data Search ("Data Search")

"統計データ検索"

Abstract:
The Data Search task focuses on the retrieval of a statistical data collection published by the Japanese government (e-Stat), and one published by the US government (Data.gov).

Website: https://ntcir.datasearch.jp/
Contact:

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Micro Activity Retrieval Task ("MART")

"Detecting microactivities in a rich multi-modal lifelogging sensor streams"

Abstract:
The NTCIR15-MAD task aims to motivate the development of a first generation of techniques for high-precision micro-activity detection and retrieval of micro-activities of daily living, to support identification and retrieval of activities that occur over short time-scales, such as minutes, rather than the long-duration event segmentation tasks of the past work. Participating researchers will develop and benchmark approaches to retrieve micro-activities from rich time-aligned multi-modal sensor data. The chosen sensors will capture a lifelog camera data stream, biosignal activity (EEG, EOG, GSR, HR) and computer accesses to record interaction with digital artefacts.

Website: http://ntcir-mart.computing.dcu.ie/
Contact:

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