Outline 1.Motivation 2.Problem statement 3.Related works 4.Baseline 5.Discussion
1. Motivation (1) A rapid expansion of e-commerce, where more and more products are sold via online portals (Amazon, eBay … ) Online product reviews thus become an important resource: – Customers to share and find opinions about products easily – Producers to get certain degrees of feedback
4. Baseline (3) Product facets identification – Association rule mining Each transaction consists of nouns/noun phrases from single sentence The frequent itemsets are the candidate product facets – Redundancy pruning Removing redundant facets that contain only single words. (e.g. life -> battery life) – Compactness pruning Removing meaningless facets that contain multiple words
4. Baseline (4) Sentiment classification – WordNet to grow seed lists of (+) and (-) ADJ – ADJ share the same orientation as their synonyms and opposite orientation as their antonyms
4. Baseline (5) Reviews labeling with facets and polarity – The unit of labeling is sentence – The summation of all these polarities yields the polarity of the whole sentence
4. Baseline (6) Summary generation – Sentences are clustered based on their labeling – For each facet, we produce a summary Sentences are scored based on concept link similarity MMR ranks the sentences
5. Discussion (1) Evaluation – We plan to carry on human evaluation.
5. Discussion (2) In the baseline, – Inherit all problems of extractive-based summary – The unit of sentence is too coarse-grained – Relationship between facets are not addressed
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