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JKISeason3-30_​tofusa

Level: Hard

Description: You work for a company that wants to improve its support for customers. Once a customer submits a question, a system should find similar questions that were submitted in the past in its database, fetch the answers that were given, and send all this data to a customer service representative. The representative should review these answers and leverage them to assist the current customer. As a first step to create this system, you should create a mechanism that recognizes whether two questions have the same intent. This will be key for finding relevant previous questions in the company’s database, leading to more effective support. Given a dataset of question pairs, annotated with whether or not they have the same intent, create a classifier that learns how to make this distinction. Hint: You can find more information about the datasets here. Hint 2: The KNIME Textprocessing extension is helpful for creating features to represent the questions.

URL: information about the datasets https://www.kaggle.com/competitions/quora-question-pairs/data
URL: Textprocessing extension https://hub.knime.com/knime/extensions/org.knime.features.ext.textprocessing/latest?pk_vid=518c74349bf716f61734176010d23a46

Level: HardDescription: You work for a company that wants to improve its support for customers. Once a customer submits a question, a system should find similar questions that were submitted in thepast in its database, fetch the answers that were given, and send all this data to a customer service representative. The representative should review these answers and leverage them toassist the current customer. As a first step to create this system, you should create a mechanism that recognizes whether two questions have the same intent. This will be key for findingrelevant previous questions in the company’s database, leading to more effective support. Given a dataset of question pairs, annotated with whether or not they have the same intent, createa classifier that learns how to make this distinction. Hint: You can find more information about the datasets here. Hint 2: The KNIME Textprocessing extension is helpful for creating featuresto represent the questions.説明 あなたは顧客サポートを改善したいと考えている企業に勤めています。顧客が質問を送信すると、システムは過去に送信された同様の質問をデータベースから検索し、その回答を取得し、このデータをすべてカスタマーサービス担当者に送信します。担当者はこれらの回答を確認し、現在の顧客を支援するために活用しなければならない。このシステムを構築する最初のステップとして、2つの質問が同じ意図を持っているかどうかを認識するメカニズムを作成する必要があります。これは、会社のデータベースから関連する過去の質問を見つけるための鍵となり、より効果的なサポートにつながります。質問ペアのデータセットが与えられ、それらが同じ意図を持っているかどうかが注釈されている場合、この区別を行う方法を学習する分類器を作成します。 Do not run all nodes at the same time, but each one at a time access zipcreate temp folderNode 2381read csv15000Q1Q2cleaningidentificationDocument1Document2vectorvectorjoinjoin15000identificationcleaningQ2Q1Document2Document1Node 2402Node 2403Node 2404joinjoinNode 2407Node 2408 ZIP ArchiveConnector Create Temp Folder Path to String(Variable) CSV Reader Partitioning Strings to Document Strings to Document String Cleaner Number to String Bag Of WordsCreator Bag Of WordsCreator Document Vector Document Vector Joiner Joiner Partitioning Number to String String Cleaner Strings to Document Strings to Document Bag Of WordsCreator Bag Of WordsCreator DocumentVector Applier DocumentVector Applier XGBoost TreeEnsemble Learner Joiner Joiner XGBoost Predictor Scorer (JavaScript) Level: HardDescription: You work for a company that wants to improve its support for customers. Once a customer submits a question, a system should find similar questions that were submitted in thepast in its database, fetch the answers that were given, and send all this data to a customer service representative. The representative should review these answers and leverage them toassist the current customer. As a first step to create this system, you should create a mechanism that recognizes whether two questions have the same intent. This will be key for findingrelevant previous questions in the company’s database, leading to more effective support. Given a dataset of question pairs, annotated with whether or not they have the same intent, createa classifier that learns how to make this distinction. Hint: You can find more information about the datasets here. Hint 2: The KNIME Textprocessing extension is helpful for creating featuresto represent the questions.説明 あなたは顧客サポートを改善したいと考えている企業に勤めています。顧客が質問を送信すると、システムは過去に送信された同様の質問をデータベースから検索し、その回答を取得し、このデータをすべてカスタマーサービス担当者に送信します。担当者はこれらの回答を確認し、現在の顧客を支援するために活用しなければならない。このシステムを構築する最初のステップとして、2つの質問が同じ意図を持っているかどうかを認識するメカニズムを作成する必要があります。これは、会社のデータベースから関連する過去の質問を見つけるための鍵となり、より効果的なサポートにつながります。質問ペアのデータセットが与えられ、それらが同じ意図を持っているかどうかが注釈されている場合、この区別を行う方法を学習する分類器を作成します。 Do not run all nodes at the same time, but each one at a time access zipcreate temp folderNode 2381read csv15000Q1Q2cleaningidentificationDocument1Document2vectorvectorjoinjoin15000identificationcleaningQ2Q1Document2Document1Node 2402Node 2403Node 2404joinjoinNode 2407Node 2408 ZIP ArchiveConnector Create Temp Folder Path to String(Variable) CSV Reader Partitioning Strings to Document Strings to Document String Cleaner Number to String Bag Of WordsCreator Bag Of WordsCreator Document Vector Document Vector Joiner Joiner Partitioning Number to String String Cleaner Strings to Document Strings to Document Bag Of WordsCreator Bag Of WordsCreator DocumentVector Applier DocumentVector Applier XGBoost TreeEnsemble Learner Joiner Joiner XGBoost Predictor Scorer (JavaScript)

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Created by: user1
Created at: 2024-05-23
On NodePit since: 2024-12-16
Last update: 2026-01-06
Created with KNIME version: v5.4.0
Tags: JKISeason3-30

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