dual attention network for product compatibility and ...hxu/aaai2018_slides.pdf · sequence...
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![Page 1: Dual Attention Network for Product Compatibility and ...hxu/aaai2018_slides.pdf · Sequence Labeling • We formalize both problems as sequence labeling problem. • Product Compatibility](https://reader034.vdocument.in/reader034/viewer/2022050608/5fafd073e38b5864e17520c7/html5/thumbnails/1.jpg)
Dual Attention Network for Product Compatibility
and Function Satisfiability AnalysisHu Xu, University of Illinois at Chicago Sihong Xie, Lehigh University Lei Shu, University of Illinois at Chicago Philip S. Yu, University of Illinois at Chicago, Tsinghua University
AAAI ’18
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I have a case and want to add a new GPU (a complementary entity).
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This is how a compatible GPU should look like.
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I found a 1070 GPU with a good price on Newegg.
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Unfortunately, the GPU (an incompatible entity) is too long to fit in… and non-
refundable.
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In the end, I damaged my case a little…
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because the case is cheaper than GPU.
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A Quiz on Complementary Entity
Google Play app store
photoshop
fallout 4
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Answer on their Compatibility
Google Play app store
photoshop
fallout 4
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Answer
Product QA is a great place for customers to resolve their compatibility concerns.
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A more general problem
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A problem about the entity “Youtube video”
Youtube video
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A problem about the entity “Youtube video”
play Youtube video
edit Youtube video
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A problem about the entity Youtube video
play Youtube video
edit Youtube video
They mean totally different functions on the same entity.
Whether a product can satisfy customers’ needs on functions is even more important.
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More QAs about Functions
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More QAs about Functions
Intrinsic Function
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More QAs about Functions
Intrinsic Function
Extrinsic Function
Extrinsic Function
Extrinsic Function
Extrinsic Function
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Roadmaps• Preliminary
• Two Closely Related Problems!
• Dual Attention Network
• Experiments
• Conclusions
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Two Closely Related Problems
• Product Compatibility Analysis (PCA)
• e.g., Works with iphone ? Yes, it is.
• Function Satisfiability Analysis (FSA)
• e.g., Works with iphone ? Yes, it is.
• In both problems, the to-be-extracted words are from the question and the polarity is in the answer.
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Sequence Labeling
• We formalize both problems as sequence labeling problem.
• Product Compatibility Analysis (PCA)
• The label space is {O, C, I, U} and C, I, U mean compatible, incompatible, and uncertain entity.
• Function Satisfiability Analysis (FSA)
• The label space is {O, S, UN, U, F-S, F-UN, F-U}
• because we want to separate function words (e.g., works with) and entities.
• S, UN, U indicate function targets (e.g., iphone, or sketching) and F-S, F-UN, F-U mean function words.
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Sequence Labeling• Product Compatibility Analysis (PCA)
• e.g., Works with iphone ?
• is labeled as O O C O
• Function Satisfiability Analysis (FSA)
• e.g., Works with iphone ?
• is labeled as F-S F-S S O
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Roadmaps• Preliminary
• Two Closely Related Problems
• Dual Attention Network!
• Experiments
• Conclusions
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Dual Attention Network
• The question and the answer can help each other to get better side-information.
• e.g., short question: “iphone ?”
• End-to-end model is preferred which incorporates the polarity from the answer into the word labels in the question.
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Dual Attention Network
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Roadmaps• Preliminary
• Two Closely Related Problems
• Dual Attention Network
• Experiments!
• Conclusions
![Page 26: Dual Attention Network for Product Compatibility and ...hxu/aaai2018_slides.pdf · Sequence Labeling • We formalize both problems as sequence labeling problem. • Product Compatibility](https://reader034.vdocument.in/reader034/viewer/2022050608/5fafd073e38b5864e17520c7/html5/thumbnails/26.jpg)
Experiment Setting• Dataset:
• We crawled 1 million electronics QAs from Amazon, combined with 8 million electronics reviews to train the word embedding.
• We annotated 7969 QA pairs from 42 products.
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Results
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Results
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Conclusions• We introduce two closely related tasks on product QA
dataset:
• Product Compatibility Analysis
• Product Function Satisfiability Analysis
• We propose Dual Attention Network, which performs attention on QA story to solve these problems.
• The datasets are available at
• https://www.cs.uic.edu/~hxu/