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20230811 Pikairos JustKNIMEIt Season 2 Challenge 20 Topics in Hotel Reviews

You work for a travel agency and want to better understand how hotels are reviewed online. What topics are common in the reviews as a whole, and what terms are most relevant in each topic? How about when you separate the reviews per rating? A colleague has already crawled and preprocessed the reviews for you, so your job now is to identify relevant topics in the reviews, and explore their key terms. What do the reviews uncover? Hint: Topic Extraction can be very helpful in tackling this challenge. Hint 2: Coherence and perplexity are metrics that can help you pick a meaningful number of topics.

Challenge 20: Topics in Hotel ReviewsDescription: You work for a travel agency and want to better understand how hotels are reviewed online. What topics arecommon in the reviews as a whole, and what terms are most relevant in each topic? How about when you separate thereviews per rating? A colleague has already crawled and preprocessed the reviews for you, so your job now is to identifyrelevant topics in the reviews, and explore their key terms. What do the reviews uncover? Hint: Topic Extraction can be veryhelpful in tackling this challenge. Hint 2: Coherence and perplexity are metrics that can help you pick a meaningful number oftopics. ProcessedReviewsPerform TopicExtractionLoop ThroughDifferent Valuesof the"noOfTopics"VariableView Chartsto DetermineBest K ValueCollectData fromAll LoopsGroup By ModelIDand Calculate theMean of theSemantic Coherenceand ExclusivityCreate a Column thatRecords thek value(noOfTopics)Add Model IDPerplexityAppendColumn toTableKeep MaxIterationLoop ThroughEach RatingIndividuallyCollectData fromAll LoopsConvertImage toTable ValueAdd RatingColumn Table Reader Topic Extractor(Parallel LDA) Parameter OptimizationLoop Start View Exclusivityand Coherence by K Loop End GroupBy ConstantValue Column Topic Scorer (Labs) ConstantValue Column Math Formula Column Appender Top k Selector Group Loop Start Loop End Image To Table Math Formula Run Topic Extractorand Create Tag Cloud View Tag Clouds Challenge 20: Topics in Hotel ReviewsDescription: You work for a travel agency and want to better understand how hotels are reviewed online. What topics arecommon in the reviews as a whole, and what terms are most relevant in each topic? How about when you separate thereviews per rating? A colleague has already crawled and preprocessed the reviews for you, so your job now is to identifyrelevant topics in the reviews, and explore their key terms. What do the reviews uncover? Hint: Topic Extraction can be veryhelpful in tackling this challenge. Hint 2: Coherence and perplexity are metrics that can help you pick a meaningful number oftopics. ProcessedReviewsPerform TopicExtractionLoop ThroughDifferent Valuesof the"noOfTopics"VariableView Chartsto DetermineBest K ValueCollectData fromAll LoopsGroup By ModelIDand Calculate theMean of theSemantic Coherenceand ExclusivityCreate a Column thatRecords thek value(noOfTopics)Add Model IDPerplexityAppendColumn toTableKeep MaxIterationLoop ThroughEach RatingIndividuallyCollectData fromAll LoopsConvertImage toTable ValueAdd RatingColumnTable Reader Topic Extractor(Parallel LDA) Parameter OptimizationLoop Start View Exclusivityand Coherence by K Loop End GroupBy ConstantValue Column Topic Scorer (Labs) ConstantValue Column Math Formula Column Appender Top k Selector Group Loop Start Loop End Image To Table Math Formula Run Topic Extractorand Create Tag Cloud View Tag Clouds

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Created by: heath
Created at: 2023-08-11
On NodePit since: 2023-08-16
Last update: 2024-11-21
Created with KNIME version: v4.7.4
Tags: JKISeason2-20Topic Extractor (Parallel LDA)Tag CloudTopic Scorer (Labs)

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